Apparatus for analysing the condition of a machine having a rotating part

ABSTRACT

A method of operating an apparatus for analysing the condition of a machine having a part rotating with a speed of rotation, includes receiving a first digital signal dependent on mechanical vibrations emanating from rotation of the part, analyzing the first digital signal So as to detect peak amplitude values during a finite time period, the finite time period corresponding to a certain amount of revolution of the part, the certain amount of revolution corresponding to more than one revolution of the monitored rotatable part, defining amplitude ranges, sorting the detected peak amplitude values into corresponding amplitude ranges so as to reflect occurrence of detected peak amplitude values within the plurality of amplitude ranges, and estimating a representative peak amplitude value in dependence on the sorted peak amplitude values and the certain amount.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention relates to a method for analysing the condition ofa machine, and to an apparatus for analysing the condition of a machine.The invention also relates to a system including such an apparatus andto a method of operating Such an apparatus. The invention also relatesto a computer program for causing a computer to perform an analysisfunction.

Description of the Related Art

Machines with moving parts are subject to wear passage of time, whichoften causes the condition with the of the machine to deteriorate.Examples of such machines with movable parts are motors, pumps,generators, compressors, lathes and CNC-machines. The movable parts maycomprise a shaft and bearings.

In order to prevent machine failure, such machines should be subject tomaintenance, depending on the condition of the machine. Therefore theoperating condition of such a machine is preferably evaluated from timeto time. The operating condition can be determined by measuringvibrations emanating from a bearing or by measuring temperature on thecasing of the machine, which temperatures are dependent on the operatingcondition of the bearing. Such condition checks of machines withrotating or other moving parts are of great significance for safety andalso for the length of the life of such machines. It is known tomanually perform such measurements on machines. This ordinarily is doneby an operator with the help of a measuring instrument performingmeasurements at measuring points on one or several machines.

A number of commercial instruments are available, which rely on the factthat defects in rolling-element bearings generate short pulses, usuallycalled shock pulses. A shock pulse measuring apparatus may generateinformation indicative of the condition of a bearing or a machine.

WO 03062766 discloses a machine having a measuring point and a shaftwith a certain shaft diameter, wherein the shaft can rotate when themachine is in use. WO 03062766 also discloses an apparatus for analysingthe condition of a machine having a rotating shaft. The disclosedapparatus has a sensor for producing a measured value indicatingvibration at a measuring point. The apparatus disclosed in WO 03062766has a data processor and a memory. The memory may store program codewhich, when run on the data processor, will cause the analysis apparatusto perform a Machine Condition Monitoring function. Such a MachineCondition Monitoring function may include shock pulse measuring.

SUMMARY OF THE INVENTION

An aspect of the invention relates to the problem of ng an improvedmethod and an improved apparatus provide for analysis of the conditionof a machine having a rotating part.

This problem is addressed by a method of operating an apparatus foranalysing the condition of a machine having a part rotating with a speedof rotation (f_(ROT)), comprising the steps of:

receiving a first digital signal (S_(RED), S_(MD), S_(ENV)) dependent onmechanical vibrations emanating from rotation of said part;

analysing said first digital signal (S_(RED), S_(MD), S_(ENV)) so as todetect peak amplitude values (Ap) during a finite time period (T_(Pm)),said finite time period corresponding to a certain amount (R) ofrevolution of said rotatable part; said certain amount (R) of revolutioncorresponding to more than one revolution of said monitored rotatablepart;

defining a plurality (N_(R)) of amplitude ranges;

sorting said detected peak amplitude values (Ap) into correspondingamplitude ranges so as to reflect occurrence (N) of detected peakamplitude values (Ap) within said plurality of amplitude ranges;

establishing a representative peak amplitude value (A_(PR)) independence on said sorted peak amplitude values (Ap) and said certainamount (R).

This solution advantageously provides a representative peak amplitudevalue A_(PR) is indicative of the mechanical state of the monitoredpart. In particular, when the monitored rotating part includes a bearingassembly, the representative peak amplitude value A_(PR) is indicativeof the mechanical State of the bearing Surfaces. In fact, therepresentative peak amplitude value A_(PR) is indicative of the degreeof roughness of the metal Surfaces in the rolling interface. Hence, therepresentative peak amplitude value (A_(PR)) may provide informationabout the presence of damage to a metal surface in the rolling interfaceof a bearing assembly. Such damage could include e.g. a crack in a metalSurface in the rolling interface of the monitored bearing assembly. Therepresentative peak amplitude value may also be indicative of spallingat a metal Surface in the rolling interface of the monitored bearingassembly. Spalling may include the flaking-off of material from asurface. The representative peak amplitude value may also be indicativeof the presence of a loose particle in the monitored bearing assembly.When there is a damage in the monitored rotating part, this solution, byfocusing on a representative peak amplitude value, provides informationindicative of the degree of damage of the most serious damage in themonitored rotating part. Hence, the representative peak amplitude valuemay be indicative of the largest spalling in a monitored rotating part.

According to an embodiment of the invention the certain amount (R) ofrevolution corresponds to several revolutions of said monitoredrotatable part. This solution advantageously provides a measurementprocedure which is very reliable in the sense that it providesrepeatable results. Hence, when the measurement procedure is repeatedlyper formed on the same rotational part so that plural monitoring periodsT_(PM1), T_(PM2), T_(PM3), T_(PM4), T_(PM5) result in measurementresults in the form of plural representative peak amplitude valuesA_(PR1), A_(PR2), A_(PR3), A_(PR4) being produced in immediate temporalSuccession, then these plural representative peak amplitude valuesA_(PR1), A_(PR2), A_(PR3), A_(PR4) have Substantially the same numericalvalue.

According to a preferred embodiment of the invention the certain amountR of revolution corresponds to at least eight revolutions of saidmonitored rotatable part so as to establish a representative peakamplitude value A_(PR), which is indicative of the mechanical state ofthe monitored part.

The problem of providing an improved method and an Improved apparatusfor analysis of the condition of a machine having a rotating part isalso addressed by an apparatus for analysing the condition of a machinehaving a part rotating with a speed of rotation (f_(ROT)), comprising:

an input for receiving a first digital signal (S_(MD)) dependent onmechanical vibrations emanating from rotation of said part;

a peak detector coupled to said input, said peak detector being adaptedto detect peak values (A_(P)) in said received first digital signal(S_(MD)), and

a burst rejector coupled to receive said detected peak values (A_(P)),said burst rejector being adapted to deliver output peak values (A_(P))on a burst rejector output in response to received detected peak values(A_(P)); and wherein

-   -   said burst rejector is adapted to control the delivery of said        output peak values (A_(PO)) such that said output peak values        (A_(P)) are delivered at a delivery frequency f_(es), wherein        -   the delivery frequency f_(es)=e*f_(ROT), wherein        -   f_(ROT) is said speed of rotation, and e is a factor having            a predetermined value.

This advantageously leads to a delivery of no more than e output peakvalues per revolution of the monitored rotating part. Hence, thissolution may advantageously reduce or eliminate bursts of amplitudepeaks which otherwise may occur. Such bursts of amplitude peaks maycause corruption of an analysis of the condition of a machine having arotating part based on detection of vibration, shock pulses and/oramplitude peak values. Bursts of amplitude peaks may be caused by impactnoise in industrial environments, i.e. bursts of amplitude peaks may becaused e.g. by an Item hitting the body of the machine having amonitored rotating part, thereby causing shock waves which travel backand forth, echoing in the body of the machine. Accordingly, Such echoingshock waves may be picked up by a sensor and reflected in the resultingsignal as a burst of amplitude peaks. In an industrial environment suchan item may be a vehicle which happens to run into the side of amachine, or a piece of metal falling onto a Surface of a machine. Hence,Such a burst of amplitude peaks may unfortunately cause corruption of apeak level analysis, unless the Impact of such bursts can be reduced oreliminated.

In an embodiment of the apparatus said burst rejector is adapted todeliver each output peak value Such that each delivered output peakamplitude value reflects the highest amplitude value detected in theimmediately pre ceding echo suppression period (T_(es)), said echosuppression period (T_(es)) being the inverse of said delivery frequencyf_(es).

In an embodiment of the apparatus the predetermined value of the factore is ten or less than ten. This advantageously leads to a delivery of nomore than ten output peak values per revolution of the monitoredrotating part.

According to an embodiment, the apparatus further comprises: means forreceiving burst rejector output peak amplitude values that have beencollected during a finite time period, said finite time periodcorresponding to a certain amount of revolution of said rotatable part;said certain amount of revolution corresponding to more than onerevolution of said monitored rotatable part;

means for sorting said peak amplitude values into a plurality ofamplitude ranges so as to reflect occurrence of detected peak amplitudevalues within said plurality of amplitude ranges; and

means for estimating a representative peak amplitude value in dependenceon said sorted peak amplitude values and said certain amount.

BRIEF DESCRIPTION OF THE DRAWINGS

For simple understanding of the present invention, described by means ofexamples and with reference it will be to the accompanying drawings, ofwhich:

FIG. 1 shows a schematic block diagram of an embodiment of a conditionanalyzing system 2 according to an embodiment of the invention includingan analysis apparatus.

FIG. 2A is a schematic block diagram of an embodiment of a part of thecondition analyzing system 2 shown in FIG. 1 including an embodiment ofan analysis apparatus.

FIG. 2B is a schematic block diagram of an embodiment of a sensorinterface.

FIG. 2C is an illustration of a measuring signal from a vibrationsensor.

FIG. 2D illustrates a measuring signal amplitude generated by a shockpulse sensor.

FIG. 2E illustrates a measuring signal amplitude generated by avibration sensor.

FIG. 3 is a simplified illustration of a Shock Pulse Measurement sensoraccording to an embodiment of the invention.

FIG. 4 is a simplified illustration of an embodiment of the memory 60and its contents.

FIG. 5 is a schematic block diagram of an embodiment of the analysisapparatus at a client location with a machine 6 having a movable shaft.

FIG. 6A illustrates a schematic block diagram of an embodiment of thepre-processor according to an embodiment of the present invention.

FIG. 6B illustrates an embodiment of the pre-processor including adigital rectifier.

FIG. 7 illustrates an embodiment of the evaluator.

FIG. 8 is a schematic illustration of a rectified signal that could bedelivered by the rectifier shown in FIG. 6B.

FIG. 9 illustrates a histogram resulting from a measurement in withoutany noise.

FIG. 10 illustrates a histogram resulting from another measurement wherehigh amplitude noise was introduced during the measurement.

FIG. 11A is a flow chart illustrating an embodiment of a method ofoperating the apparatus so as to set it up for performing peak levelcondition analysis.

FIG. 11B is a flow chart illustrating an embodiment of a method ofoperating the apparatus so as to perform peak level condition analysis.

FIG. 12A is a flow chart illustrating an embodiment of a method ofperforming a peak level measurement session.

FIG. 12B is a flow chart illustrating an embodiment of a method ofperforming a peak level measurement session and addressing the impact ofbursts of noise amplitude peaks.

FIG. 13A illustrates a histogram having plural amplitude bins.

FIG. 13B is a schematic illustration of plural memory positions arrangedas a table.

FIG. 13C is an illustration of a cumulative histogram tablecorresponding to the histogram table of FIG. 13B.

FIG. 14A is a flow chart illustrating an embodiment of a method forestablishing a representative peak amplitude value on the basis of thepeak amplitude values Ap collected in the measurement session.

FIG. 14B is a flow chart illustrating yet an embodiment of a method forestimating a representative peak amplitude value A_(PR) on the basis ofthe peak amplitude values Ap collected in the measurement session.

FIG. 15A is an illustration reflecting the principle of a cumulativehistogram resulting from a measurement.

FIG. 16 is a schematic block diagram of an embodiment of the analysisapparatus.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

In the following description similar features in different embodimentsmay be indicated by the same reference numerals.

FIG. 1 shows a schematic block diagram of an embodiment of a conditionanalyzing system 2 according to an embodiment of the invention.Reference numeral 4 relates to a client location with a machine 6 havinga movable part 8. The movable part may comprise bearings 7 and a shaft 8which, when the machine is in operation, rotates. The operatingcondition of the shaft 8 or of a bearing 7 can be determined in responseto vibrations emanating from the shaft and/or bearing when the shaftrotates. The client location 4, which may also be referred to as clientpart or user part, may for example be the premises of a wind farm, i.e.a group of wind turbines at a location, or the premises of a paper millplant, or some other manufacturing plant having machines with movableparts.

An embodiment of the condition analyzing system 2 is operative when asensor 10 is attached on or at a measuring point 12 on the body of themachine 6. Although FIG. 1 only illustrates two measuring points 12, itto be understood that a location 4 may comprise any number of measuringpoints 12. The condition analysis system 2 shown in FIG. 1, comprises ananalysis apparatus 14 for analysing the condition of a machine on thebasis of measurement values delivered by the sensor 10.

The analysis apparatus 14 has a communication port 16 for bi-directionaldata exchange. The communication port 16 is connectable to acommunications network 18, e.g. via a data interface 19. Thecommunications network 18 may be the world wide internet, also known asthe Internet. The communications network 18 may also comprise a publicswitched telephone network.

A server computer 20 is connected to the communications network 18. Theserver 20 may comprise a database 22, user input/output interfaces 24and data processing hardware 26, and a communications port 29. Theserver computer 20 is located on a location 28, which is geographicallyseparate from the client location 4. The server location 28 may be in afirst city, such as the Swedish capital Stockholm, and the clientlocation may be in another city, such as Stuttgart, Germany or Detroitin Michigan, USA. Alternatively, the server location 28 may be in afirst part of a town and the client location may be in another part ofthe same town. The server location 28 may also be referred to assupplier part 28, or supplier part location 28.

According to an embodiment of the invention a central control location31 comprises a control computer 33 having data processing hardware andsoftware for surveying a plurality of machines at the client location 4.The machines 6 may be wind turbines or gear boxes used in wind turbines.Alternatively the machines may include machinery in e.g. a paper mill.The control computer 33 may comprise a database 22B, user input/outputinterfaces 24B and data processing hardware 26B, and a communicationsport 29B. The central control location 31 may be separated from theclient location 4 by a geographic distance. By means of communicationsport 29B the control computer 33 can be coupled to communicate withanalysis apparatus 14 via port 16. The analysis apparatus 14 may delivermeasurement data being partly processed so as to allow further signalprocessing and/or analysis to be performed at the central location 31 bycontrol computer 33.

A supplier company occupies the supplier part location 28. The suppliercompany may sell and deliver analysis apparatuses 14 and/or software foruse in an analysis apparatus 14. The supplier company may also sell anddeliver analysis software for use in the control computer at the centralcontrol location 31. Such analysis software 94,105 is discussed inconnection with FIG. 4 below. Such analysis software 94,105 may bedelivered by transmission over said communications network 18.

According to one embodiment of the system 2 the apparatus 14 is aportable apparatus which may be connected to the communications network18 from time to time.

According to another embodiment of the system 2 the apparatus 14 isconnected to the communications network 18 substantially continuously.Hence, the apparatus 14 according to this embodiment may substantiallyalways be “on line” available for communication with the suppliercomputer 20 and/or with the control computer 33 at control location 31.

FIG. 2A is a schematic block diagram of an embodiment of a part of thecondition analyzing system 2 shown in FIG. 1. The condition analyzingsystem, as illustrated in FIG. 2A, comprises a sensor unit 10 forproducing a measured value. The measured value may be dependent onmovement or, more precisely, dependent on vibrations or shock pulsescaused by bearings when the shaft rotates.

An embodiment of the condition analyzing system 2 is operative when adevice 30 is firmly mounted on or at a measuring point on a machine 6.The device 30 mounted at the measuring point may be referred to as astud 30. A stud 30 can comprise a connection coupling 32 to which thesensor unit 10 is removably attachable. The connection coupling 32 can,for example comprise double start threads for enabling the sensor unitto be mechanically engaged with the stud by means of a ¼ turn rotation.

A measuring point 12 can comprise a threaded recess in the casing of themachine. A stud 30 may have a protruding part with threads correspondingto those of the recess for enabling the stud to be firmly attached tothe measuring point by introduction into the recess like a bolt.

Alternatively, a measuring point can comprise a threaded recess in thecasing of the machine, and the sensor unit 10 may comprise correspondingthreads so that it can be directly introduced into the recess.Alternatively, the measuring point is marked on the casing of themachine only with a painted mark.

The machine 6 exemplified in FIG. 2A may have a rotating shaft with acertain shaft diameter d1. The shaft in the machine 24 may rotate with aspeed of rotation V1 when the machine 6 is in use.

The sensor unit 10 may be coupled to the apparatus 14 for analysing thecondition of a machine. With reference to FIG. 2A, the analysisapparatus 14 comprises a sensor interface 40 for receiving a measuredsignal or measurement data, produced by the sensor 10. The sensorinterface 40 is coupled to a data processing means 50 capable ofcontrolling the operation of the analysis apparatus 14 in accordancewith program code. The data processing means 50 is also coupled to amemory 60 for storing said program code.

According to an embodiment of the Invention the sensor interface 40comprises an input 42 for receiving an analogue signal, the input 42being connected to an analogue-to-digital (A/D) converter 44, thedigital output 48 of which is coupled to the data processing means 50.The A/D converter 44 samples the received analogue signal with a certainsampling frequency f_(S) so as to deliver a digital measurement datasignal S_(MD) having said certain sampling frequency f_(S) and whereinthe amplitude of each sample depends on the amplitude of the receivedanalogue signal at the moment of sampling.

According to another embodiment of the invention, illustrated in FIG.2B, the sensor interface 40 comprises an input 42 for receiving ananalogue signal S_(EA) from a Shock Pulse Measurement Sensor, aconditioning circuit 43 coupled to receive the analogue signal, and anA/D converter 44 coupled to receive the conditioned analogue signal fromthe conditioning circuit 43. The A/D converter 44 samples the receivedconditioned analogue signal with a certain sampling frequency f_(S) soas to deliver a digital measurement data signal S_(MD) having saidcertain sampling frequency f_(S) and wherein the amplitude of eachsample depends on the amplitude of the received analogue signal at themoment of sampling.

The sampling theorem guarantees that bandlimited signals (i.e., signalswhich have a maximum frequency) can be reconstructed perfectly fromtheir sampled version, if the sampling rate f_(S) is more than twice themaximum frequency f_(SEAmax) of the analogue signal S_(EA) to bemonitored. The frequency equal to one-half of the sampling rate istherefore a theoretical limit on the highest frequency that can beunambiguously represented by the sampled signal S_(MD). This frequency(half the sampling rate) is called the Nyquist frequency of the samplingsystem. Frequencies above the Nyquist frequency f_(N) can be observed inthe sampled signal, but their frequency is ambiguous. That is, afrequency component with frequency f cannot be distinguished from othercomponents with frequencies B*f_(N)+f, and

B*f _(N) −f

for nonzero integers B. This ambiguity, known as aliasing may be handledby filtering the signal with an anti-aliasing filter (usually a low-passfilter with cutoff near the Nyquist frequency) before conversion to thesampled discrete representation.

In order to provide a safety margin for in terms of allowing a non-idealfilter to have a certain slope in the frequency response, the samplingfrequency may be selected to a higher value than 2. Hence, according toembodiments of the invention the sampling frequency may be set to

f _(S) =k*f _(SEAmax)

wherein

k is a factor having a value higher than 2.0

Accordingly the factor k may be selected to a value higher than 2.0.Preferably factor k may be selected to a value between 2.0 and 2.9 inorder to provide a good safety margin while avoiding to generateunnecessarily many sample values. According to an embodiment the factork is advantageously selected such that 100*k/2 renders an integer.According to an embodiment the factor k may be set to 2.56. Selecting kto 2.56 renders 100*k=256=2 raised to 8.

According to an embodiment the sampling frequency f_(S) of the digitalmeasurement data signal S_(MD) may be fixed to a certain value f_(S),such as e.g. f_(S)=102 kHz

Hence, when the sampling frequency f_(S) is fixed to a certain valuef_(S), the maximum frequency f_(SEAmax) of the analogue signal S_(EA)will be:

f _(SEAmax) =f _(S) /k

wherein f_(SEAmax) is the highest frequency to be analyzed in thesampled signal

Hence, when the sampling frequency f_(S) is fixed to a certain valuef_(S)=102 400 Hz, and the factor k is set to 2.56, the maximum frequencyf_(SEAmax) of the analogue signal S_(EA) will be:

f _(SEAmax) =f _(S) /k=102400/2,56=40 kHz

Accordingly, a digital measurement data signal S_(MD), having a certainsampling frequency f_(S), is generated in response to said receivedanalogue measurement signal S_(EA). The digital output 48 of the A/Dconverter 44 is coupled to the data processing means 50 via an output 49of the sensor interface 40 so as to deliver the digital measurement datasignal S_(MD) to the data processing means 50.

The sensor unit 10 may comprise a vibration transducer, the sensor unitbeing structured to physically engage the connection coupling of themeasuring point so that vibrations of the machine at the measuring pointare transferred to the vibration transducer. According to an embodimentof the invention the sensor unit comprises a transducer having apiezo-electric element. When the measuring point 12 vibrates, the sensorunit 10, or at least a part of it, also vibrates and the transducer thenproduces an electrical signal of which the frequency and amplitudedepend on the mechanical vibration frequency and the vibration amplitudeof the measuring point 12, respectively. According to an embodiment ofthe invention the sensor unit 10 is a vibration sensor, providing ananalogue amplitude signal of e.g. 10 mV/g in the Frequency Range 1.00 to10000 Hz. Such a vibration sensor is designed to deliver substantiallythe same amplitude of 10 mV irrespective of whether it is exerted to theacceleration of 1 g (9.82 m/s²) at 1 Hz, 3 Hz or 10 Hz. Hence, a typicalvibration sensor has a linear response in a specified frequency range upto around 10 kHz. Mechanical vibrations in that frequency rangeemanating from rotating machine parts are usually caused by imbalance ormisalignment. However, when mounted on a machine the linear responsevibration sensor typically also has several different mechanicalresonance frequencies dependent on the physical path between sensor andvibration source.

A damage in a roller bearing may cause relatively sharp elastic waves,known as shock pulses, travelling along a physical path in the housingof a machine before reaching the sensor. Such shock pulses often have abroad frequency spectrum. The amplitude of a roller bearing shock pulseis typically lower than the amplitude of a vibration caused by imbalanceor misalignment.

The broad frequency spectrum of shock pulse signatures enables them toactivate a “ringing response” or a resonance at a resonance frequencyassociated with the sensor.

Hence, a typical measuring signal from a vibration sensor may have awave form as shown in FIG. 2C, i.e. a dominant low frequency signal witha superimposed higher frequency lower amplitude resonant “ringingresponse”.

In order to enable analysis of the shock pulse signature, oftenemanating from a bearing damage, the low frequency component must befiltered out. This can be achieved by means of a high pass filter or bymeans of a band pass filter. However, these filters must be adjustedsuch that the low frequency signal portion is blocked while the highfrequency signal portion is passed on. An individual vibration sensorwill typically have one resonance frequency associated with the physicalpath from one shock pulse signal source, and a different resonancefrequency associated with the physical path from another shock pulsesignal source, as mentioned in U.S. Pat. No. 6,053,047. Hence, filteradjustment aiming to pass the high frequency signal portion requiresindividual adaptation when a vibration sensor is used.

When such filter is correctly adjusted the resulting signal will consistof the shock pulse signature(s). However, the analysis of the shockpulse signature(s) emanating from a vibration sensor is somewhatimpaired by the fact that the amplitude response as well as resonancefrequency inherently varies dependent on the individual physical pathfrom the shock pulse signal sources.

Advantageously, these drawbacks associated with vibration sensors may bealleviated by the use of a Shock Pulse Measurement sensor. The ShockPulse Measurement sensor is designed and adapted to provide apredetermined mechanical resonance frequency, as described in furtherdetail below.

This feature of the Shock Pulse Measurement sensor advantageouslyrenders repeatable measurement results in that the output signal from aShock Pulse Measurement sensor has a stable resonance frequencysubstantially independent of the physical path between the shock pulsesignal source and the shock pulse sensor. Moreover, mutually differentindividual shock pulse sensors provide a very small, if any, deviationin resonance frequency.

An advantageous effect of this is that signal processing is simplified,in that filters need not be individually adjusted, in contrast to thecase described above when vibration sensors are used. Moreover, theamplitude response from shock pulse sensors is well defined such that anindividual measurement provides reliable information when measurement isperformed in accordance with appropriate measurement methods defined byS.P.M. Instrument AB.

FIG. 2D illustrates a measuring signal amplitude generated by a shockpulse sensor, and FIG. 2E illustrates a measuring signal amplitudegenerated by a vibration sensor. Both sensors have been exerted to thesame series of mechanical shocks without the typical low frequencysignal content. As clearly seen in FIGS. 2D and 2E, the duration of aresonance response to a shock pulse signature from the Shock PulseMeasurement sensor is shorter than the corresponding resonance responseto a shock pulse signature from the vibration sensor.

This feature of the Shock Pulse Measurement sensor of providing distinctshock pulse signature responses has the advantageous effect of providinga measurement signal from which it is possible to distinguish betweendifferent mechanical shock pulses that occur within a short time span.

According to an embodiment of the invention the sensor is a Shock PulseMeasurement sensor. FIG. 3 is a simplified illustration of a Shock PulseMeasurement sensor 10 according to an embodiment of the invention.According to this embodiment the sensor comprises a part 110 having acertain mass or weight and a piezo-electrical element 120. Thepiezo-electrical element 120 is somewhat flexible so that it cancontract and expand when exerted to external force. The piezo-electricalelement 120 is provided with electrically conducting layers 130 and 140,respectively, on opposing surfaces. As the piezo-electrical element 120contracts and expands it generates an electric signal which is picked upby the conducting layers 130 and 140. Accordingly, a mechanicalvibration is transformed into an analogue electrical measurement signalS_(EA), which is delivered on output terminals 145, 150.

The piezo-electrical element 120 may be positioned between the weight110 and a surface 160 which, during operation, is physically attached tothe measuring point 12, as illustrated in FIG. 3.

The Shock Pulse Measurement sensor 10 has a resonance frequency thatdepends on the mechanical characteristics for the sensor, such as themass m of weight part 110 and the resilience of piezo-electrical element120. Hence, the piezo-electrical element has an elasticity and a springconstant k. The mechanical resonance frequency f_(RM) for the sensor istherefore also dependent on the mass m and the spring constant k.

According to an embodiment of the Invention the mechanical resonancefrequency f_(RM) for the sensor can be determined by the equationfollowing equation:

f _(RM)=1(2T)√{square root over ((k/m))}  (eq1)

According to another embodiment the actual mechanical resonancefrequency for a Shock Pulse Measurement sensor 10 may also depend onother factors, such as the nature of the attachment of the sensor 10 tothe body of the machine 6.

The resonant Shock Pulse Measurement sensor 10 is thereby particularlysensitive to vibrations having a frequency on or near the mechanicalresonance frequency f_(RM) The Shock Pulse Measurement sensor 10 may bedesigned so that the mechanical resonance frequency f_(RM) is somewherein the range from 28 kHz to 37 kHz. According to another embodiment themechanical resonance frequency f_(RM) is somewhere in the range from 30kHz to 35 kHz.

Accordingly the analogue electrical measurement signal has an electricalamplitude which may vary over the frequency spectrum. For the purpose ofdescribing the theoretical background, it may be assumed that if theShock Pulse Measurement sensor 10 were exerted to mechanical vibrationswith identical amplitude in all frequencies from e.g. 1 Hz to e.g. 200000 kHz, then the amplitude of the analogue signal S_(EA) from the ShockPulse Measurement Sensor will have a maximum at the mechanical resonancefrequency f_(RM), since the sensor will resonate when being “pushed”with that frequency.

With reference to FIG. 2B, the conditioning circuit 43 receives theanalogue signal S_(EA). The conditioning circuit 43 may be designed tobe an impedance adaption circuit designed to adapt the input impedanceof the A/D-converter as seen from the sensor terminals 145,150 so thatan optimum signal transfer will occur. Hence, the conditioning circuit43 may operate to adapt the input impedance Z_(in) as seen from thesensor terminals 145,150 so that a maximum electric power is deliveredto the A/D-converter 44. According to an embodiment of the conditioningcircuit 43 the analogue signal S_(EA) is fed to the primary winding of atransformer, and a conditioned analogue signal is delivered by asecondary winding of the transformer. The primary winding has n1 turnsand the secondary winding has n2 turns, the ratio n1/n2=n₁₂. Hence, theA/D converter 44 is coupled to receive the conditioned analogue signalfrom the conditioning circuit 43. The A/D converter 44 has an inputimpedance Z₄₄, and the input impedance of the A/D-converter as seen fromthe sensor terminals 145,150 will be (n1/n2)²*Z₄₄, when the conditioningcircuit 43 is coupled in between the sensor terminals 145,150 and theinput terminals of the A/D converter 44.

The A/D converter 44 samples the received conditioned analogue signalwith a certain sampling frequency f_(S) so as to deliver a digitalmeasurement data signal S_(MD) having said certain sampling frequencyf_(S) and wherein the amplitude of each sample depends on the amplitudeof the received analogue signal at the moment of sampling.

According to embodiments of the invention the digital measurement datasignal S_(MD) is delivered to a means 180 for digital signal processing(See FIG. 5).

According to an embodiment of the invention the means 180 for digitalsignal processing comprises the data processor 50 and program code forcausing the data processor 50 to perform digital signal processing.According to an embodiment of the invention the processor 50 is embodiedby a Digital Signal Processor. The Digital Signal Processor may also bereferred to as a DSP.

With reference to FIG. 2A, the data processing means 50 is coupled to amemory 60 for storing said program code. The program memory 60 ispreferably a non-volatile memory. The memory 60 may be a read/writememory, i.e. enabling both reading data from the memory and writing newdata onto the memory 60. According to an embodiment the program memory60 is embodied by a FLASH memory. The program memory 60 may comprise afirst memory segment 70 for storing a first set of program code 80 whichis executable so as to control the analysis apparatus 14 to performbasic operations (FIG. 2A and FIG. 4). The program memory may alsocomprise a second memory segment 90 for storing a second set of programcode 94. The second set of program code 94 in the second memory segment90 may include program code for causing the analysis apparatus toprocess the detected signal, or signals, so as to generate apre-processed signal or a set of pre-processed signals. The memory 60may also include a third memory segment 100 for storing a third set ofprogram code 104. The set of program code 104 in the third memorysegment 100 may include program code for causing the analysis apparatusto perform a selected analysis function 105. When an analysis functionis executed it may cause the analysis apparatus to present acorresponding analysis result on user interface 106 or to deliver theanalysis result on port 16 (See FIG. 1 and FIG. 2A and FIG. 7).

The data processing means 50 is also coupled to a read/write memory 52for data storage. Moreover, the data processing means 50 may be coupledto an analysis apparatus communications interface 54. The analysisapparatus communications interface 54 provides for bi-directionalcommunication with a measuring point communication interface 56 which isattachable on, at or in the vicinity of the measuring point on themachine.

The measuring point 12 may comprise a connection coupling 32, a readableand writeable information carrier 58, and a measuring pointcommunication interface 56.

The writeable information carrier 58, and the measuring pointcommunication interface 56 may be provided in a separate device 59placed in the vicinity of the stud 30, as illustrated in FIG. 2.Alternatively the writeable information carrier 58, and the measuringpoint communication interface 56 may be provided within the stud 30.This is described in more detail in WO 98/01831, the content of which ishereby incorporated by reference.

The system 2 is arranged to allow bidirectional communication betweenthe measuring point communication interface 56 and the analysisapparatus communication interface 54. The measuring point communicationinterface 56 and the analysis apparatus communication interface 54 arepreferably constructed to allow wireless communication. According to anembodiment the measuring point communication interface and the analysisapparatus communication interface are constructed to communicate withone another by radio frequency (RF) signals. This embodiment includes anantenna in the measuring point communication interface 56 and anotherantenna the analysis apparatus communication interface 54.

FIG. 4 is a simplified illustration of an embodiment of the memory 60and its contents. The simplified illustration is intended to conveyunderstanding of the general idea of storing different program functionsin memory 60, and it is not necessarily a correct technical teaching ofthe way in which a program would be stored in a real memory circuit. Thefirst memory segment 70 stores program code for controlling the analysisapparatus 14 to perform basic operations. Although the simplifiedillustration of FIG. 4 shows pseudo code, it is to be understood thatthe program code 80 may be constituted by machine code, or any levelprogram code that can be executed or interpreted by the data processingmeans 50 (FIG. 2A).

The second memory segment 90, illustrated in FIG. 4, stores a second setof program code 94. The program code 94 in segment 90, when run on thedata processing means 50, will cause the analysis apparatus 14 toperform a function, such as a digital signal processing function. Thefunction may comprise an advanced mathematical processing of the digitalmeasurement data signal S_(MD). According to embodiments of theinvention the program code 94 is adapted to cause the processor means 50to perform signal processing functions described in connection withFIGS. 5, 6, 9, 10, 11A, 11B, 12A, 12B, 13A-C, 14A, 14B, 15A and/or FIG.16 in this document.

As mentioned above in connection with FIG. 1, a computer program forcontrolling the function of the analysis apparatus may be downloadedfrom the server computer 20. This means that theprogram-to-be-downloaded is transmitted to over the communicationsnetwork 18. This can be done by modulating a carrier wave to carry theprogram over the communications network 18. Accordingly the down-loadedprogram may be loaded into a digital memory, such as memory 60 (SeeFIGS. 2A and 4). Hence, a signal processing program 94 and or ananalysis function program 104, 105 may be received via a communicationsport, such as port 16 (FIGS. 1 & 2A), so as to load it into memory 60.Similarly, a signal processing program 94 and or an analysis functionprogram 104, 105 may be received via communications port 29B (FIG. 1),so as to load it into a program memory location in computer 26B or indatabase 22B.

An aspect of the invention relates to a computer program product, suchas a program code means 94 and/or program code means 104, 105 loadableinto a digital memory of an apparatus. The computer program productcomprising software code portions for performing signal processingmethods and/or analysis functions when said product is run on a dataprocessing unit 50 of an apparatus for analysing the condition of amachine. The term “run on a data processing unit” means that thecomputer program plus the data processing unit carries out a method ofthe kind described in this document.

The wording “a computer program product, load-able into a digital memoryof a condition analysing apparatus” means that a computer program can beintroduced into a digital memory of a condition analysing apparatus soas achieve a condition analysing apparatus programmed to be capable of,or adapted to, carrying out a method of the kind described above. Theterm “loaded into a digital memory of a condition analysing apparatus”means that the condition analysing apparatus programmed in this way iscapable of, or adapted to, carrying out a method of the kind describedabove.

The above mentioned computer program product may also be loadable onto acomputer readable medium, such as a compact disc or DVD. Such a computerreadable medium may be used for delivery of the program to a client.

According to an embodiment of the analysis apparatus 14 (FIG. 2A), itcomprises a user input interface 102, whereby an operator may interactwith the analysis apparatus 14. According to an embodiment the userinput interface 102 comprises a set of buttons 104. An embodiment of theanalysis apparatus 14 comprises a user output interface 106. The useroutput interface may comprise a display unit 106. The data processingmeans 50, when it runs a basic program function provided in the basicprogram code 80, provides for user interaction by means of the userinput interface 102 and the display unit 106. The set of buttons 104 maybe limited to a few buttons, such as for example five buttons, asillustrated in FIG. 2A. A central button 107 may be used for an ENTER orSELECT function, whereas other, more peripheral buttons may be used formoving a cursor on the display 106. In this manner it is to beunderstood that symbols and text may be entered into the apparatus 14via the user interface. The display unit 106 may, for example, display anumber of symbols, such as the letters of alphabet, while the cursor ismovable on the display in response to user input so as to allow the userto input information.

FIG. 5 is a schematic block diagram of an embodiment of the analysisapparatus 14 at a client location 4 with a machine 6 having a movableshaft 8. The sensor 10, which may be a Shock Pulse Measurement Sensor,is shown attached to the body of the machine 6 so as to pick upmechanical vibrations and so as to deliver an analogue measurementsignal S_(EA) indicative of the detected mechanical vibrations to thesensor interface 40. The sensor interface 40 may be designed asdescribed in connection with FIG. 2A or 2B. The sensor interface 40delivers a digital measurement data signal S_(MD) to a means 180 fordigital signal processing.

The digital measurement data signal S_(MD) has a sampling frequencyf_(S), and the amplitude value of each sample depends on the amplitudeof the received analogue measurement signal S_(EA) at the moment ofsampling. According to an embodiment the sampling frequency f_(S) of thedigital measurement data signal S_(MD) may be fixed to a certain valuef_(S), such as e.g. f_(S)=102 400 Hz. The sampling frequency f_(S) maybe controlled by a clock signal delivered by a clock 190, as illustratedin FIG. 5. The clock signal may also be delivered to the means 180 fordigital signal processing. The means 180 for digital signal processingcan produce information about the temporal duration of the receiveddigital measurement data signal S_(MD) in response to the receiveddigital measurement data signal S_(MD), the clock signal and therelation between the sampling frequency f_(S) and the clock signal,since the duration between two consecutive sample values equalsTs=1/f_(S).

According to embodiments of the invention the means 180 for digitalsignal processing includes a pre-processor 200 for performing apre-processing of the digital measurement data signal S_(MD) so as todeliver a pre-processed digital signal S_(MDP) on an output 210. Theoutput 210 is coupled to an input 220 of an evaluator 230. The evaluator230 is adapted to evaluate the pre-processed digital signal S_(MDP) soas to deliver a result of the evaluation to a user interface 106.Alternatively the result of the evaluation may be delivered to acommunication port 16 so as to enable the transmission of the resulte.g. to a control computer 33 at a control site 31 (See FIG. 1).

According to an embodiment of the invention, the functions described inconnection with the functional blocks in means 180 for digital signalprocessing, pre-processor 200 and evaluator 230 may be embodied bycomputer program code 94 and/or 104 as described in connection withmemory blocks 90 and 100 in connection with FIG. 4 above.

A user may require only a few basic monitoring functions for detectionof whether the condition of a machine is normal or abnormal. Ondetecting an abnormal condition, the user may call for specializedprofessional maintenance personnel to establish the exact nature of theproblem, and for performing the necessary maintenance work. Theprofessional maintenance personnel frequently needs and uses a broadrange of evaluation functions making it possible to establish the natureof, and/or cause for, an abnormal machine condition. Hence, differentusers of an analysis apparatus 14 may pose very different demands on thefunction of the apparatus. The term Condition Monitoring function isused in this document for a function for detection of whether thecondition of a machine is normal or somewhat deteriorated or abnormal.The term Condition Monitoring function also comprises an evaluationfunction making it possible to establish the nature of, and/or causefor, an abnormal machine condition.

Examples of Machine Condition Monitoring Functions

The condition monitoring functions F1, F2 . . . Fn includes functionssuch as: vibration analysis, shock pulse measuring, Peak level analysis,spectrum analysis of shock pulse measurement data, Fast FourierTransformation of vibration measurement data, graphical presentation ofcondition data on a user interface, storage of condition data in awriteable information carrier on said machine, storage of condition datain a writeable information carrier in said apparatus, tachometering,imbalance detection, and mis-aligmnent detection.

According to an embodiment the apparatus 14 includes the followingfunctions:

-   -   F1=vibration analysis;    -   F2=shock pulse measuring,    -   F3=Peak level analysis    -   F4=spectrum analysis of shock pulse measurement data,    -   F5=Fast Fourier Transformation of vibration measurement data,    -   F6=graphical presentation of condition data on a user interface,    -   F7=storage of condition data m a writeable information carrier        on said machine,    -   F8=storage of condition data m a writeable information carrier        52 in said apparatus,    -   F9=tachometering,    -   F10=Imbalance detection, and    -   F11=misalignment detection.    -   F12=Retrieval of condition data from a writeable information        carrier 58 on said machine.    -   F13=Performing Peak level analysis F3 and performing function        F12 “Retrieval of condition data from a writeable information        carrier 58 on said machine” so as to enable a comparison or        trending based on current Peak level data and historical Peak        level data.    -   F14=Retrieval of identification data from a writeable        information carrier 58 on said machine.

Embodiments of the function F7 “storage of condition data in a writeableinformation carrier on said machine”, and F13 vibration analysis andretrieval of condition data is described in more detail in WO 98/01831,the content of which is hereby incorporated by reference.

The peak level analysis F3 may be performed on the basis of theenveloped time domain signal S_(ENV) delivered by the enveloper 250. Thesignal S_(ENV) is also referred to as S_(MDP). The peak level analysisF3 is adapted to monitor the signal for the duration of a peakmonitoring period P_(PM) for the purpose of establishing the maximumamplitude level.

The peak amplitude may be indicative of Oil film thickness in amonitored bearing. Hence, the detected peak amplitude may be indicativeof separation between the metal surfaces in the rolling interface. Theoil film thickness may depend on lubricant supply and/or on alignment ofthe shaft. Moreover, the oil film thickness may depend on the load onthe shaft, i.e. on the force with which metal surfaces are pressedtogether, the metal surfaces being e.g. that of a bearing and that of ashaft.

The actual detected value of the maximum amplitude level may also dependon the mechanical state of the bearing surfaces, i.e., the condition ofthe bearing assembly. Accordingly, the detected value of the maximumamplitude level may depend on roughness of the metal surfaces in therolling interface, and/or damage to a metal surface in the rollinginterface. The detected value of the maximum amplitude level may alsodepend on the occurrence of a loose particle in the bearing assembly.

FIG. 6A illustrates a schematic block diagram of an embodiment of thepre-processor 200 according to an embodiment of the present invention.In this embodiment the digital measurement data signal S_(MD) is coupledto a digital band pass filter 240 having a lower cutoff frequency fir anupper cutoff frequency f_(UC) and passband bandwidth between the upperand lower cutoff frequencies.

The output from the digital band pass filter 240 is connected to adigital enveloper 250. According to an embodiment of the invention thesignal output from the enveloper 250 is delivered to an output 260. Theoutput 260 of the pre-processor 200 is coupled to output 210 of digitalsignal processing means 180 for delivery to the input 220 of evaluator230.

The upper and lower cutoff frequencies of the digital band pass filter240 may selected so that the frequency components of the signal S_(MD)at the resonance frequency f_(RM) for the sensor are in the passbandbandwidth. As mentioned above, an amplification of the mechanicalvibration is achieved by the sensor being mechanically resonant at theresonance frequency f_(RM). Accordingly the analogue measurement signalS_(EA) reflects an amplified value of the vibrations at and around theresonance frequency f_(RM). Hence, the band pass filter according to theFIG. 6 embodiment advantageously suppresses the signal at frequenciesbelow and above resonance frequency f_(RM), so as to further enhance thecomponents of the measurement signal at the resonance frequency f_(RM).Moreover, the digital band pass filter 240 advantageously furtherreduces noise inherently included in the measurement signal, since anynoise components below the lower cutoff frequency f_(LC) and above uppercutoff frequency f_(UC) are also eliminated or reduced. Hence, whenusing a resonant Shock Pulse Measurement sensor 10 having a mechanicalresonance frequency f_(RM) in a range from a lowest resonance frequencyvalue f_(RML) to a highest resonance frequency value f_(RMU) the digitalband pass filter 240 may be designed to having a lower cutoff frequencyf_(LC)=f_(RM), and an upper cutoff frequency f_(UC)=f_(RMU). Accordingto an embodiment the lower cutoff frequency f_(LC)=f_(RML)=28 kHz, andthe upper cutoff frequency f_(UC)=f_(RMU)=37 kHz.

According to another embodiment the mechanical resonance frequencyf_(RM) is somewhere in the range from 30 kHz to 35 kHz, and the digitalband pass filter 240 may then be designed to having a lower cutofffrequency f_(LC)=30 kHz and an upper cutoff frequency f_(UC)35 kHz.

According to another embodiment the digital band pass filter 240 may bedesigned to have a lower cutoff frequency F_(LC) being lower than thelowest resonance frequency value f_(RM), and an upper cutoff frequencyf_(UC) being higher than the highest resonance frequency value f_(RMU).For example the mechanical resonance frequency f_(RM) may be a frequencyin the range from 30 kHz to 35 kHz, and the digital band pass filter 240may then be designed to having a lower cutoff frequency f_(LC)=17 kHz,and an upper cutoff frequency f_(UC)=36 kHz.

Accordingly, the digital band pass filter 240 may deliver a passbanddigital measurement data signal S_(F) having an advantageously lowout-of-band noise content and reflecting mechanical vibrations in thepassband. The passband digital measurement data signal S_(F) may bedelivered to an enveloper 250.

The digital enveloper 250 accordingly receives the passband digitalmeasurement data signal S_(F) which may reflect a signal having positiveas well as negative amplitudes. With reference to FIG. 6A, the receivedsignal is rectified by a digital rectifier 270, and the rectified signalmay be filtered by an optional low pass filter 280 so as to produce adigital envelop signal S_(ENV).

Accordingly, the signal S_(ENV) is a digital representation of anenvelope signal being produced in response to the filtered measurementdata signal S_(F). According to some embodiments of the Invention theoptional low pass filter 280 may be eliminated.

According to the FIG. 6A embodiment of the invention the signal S_(ENV)is delivered to the output 260 of pre-processor 200. Hence, according toan embodiment of the Invention the pre-processed digital signal S_(MDP)delivered on the output 210 (FIG. 5) is the digital envelop signalS_(ENV).

Whereas prior art analogue devices for generating an envelop signal inresponse to a measurement signal employs an analogue rectifier whichinherently leads to a biasing error being introduced in the resultingsignal, the digital enveloper 250 will advantageously produce a truerectification without any biasing errors. Accordingly, the digitalenvelop signal S_(ENV) will have a good Signal-to-Noise Ratio, since thesensor being mechanically resonant at the resonance frequency in thepassband of the digital band pass filter 240 leads to a high signalamplitude and the signal processing being performed in the digitaldomain eliminates addition of noise and eliminates addition of biasingerrors.

With reference to FIG. 5 the pre-processed digital signal S_(MDP) isdelivered to input 220 of the evaluator 230.

According to another embodiment, the filter 240 is a high pass filterhaving a cut-off frequency f_(LC). This embodiment simplifies the designby replacing the band-pass filter with a high-pass filter 240, therebyleaving the low pass filtering to another low pass filter downstream,such as the low pass filter 280. The cut-off frequency f_(LC) of thehigh pass filter 240 is selected to approximately the value of thelowest expected mechanical resonance frequency value f_(RMU) of theresonant Shock Pulse Measurement sensor 10. When the mechanicalresonance frequency f_(RM) is somewhere in the range from 30 kHz to 35kHz, the high pass filter 240 may be designed to having a lower cutofffrequency f_(LC)=30 kHz. The high-pass filtered signal is then passed tothe rectifier 270 and on to the low pass filter 280.

According to an embodiment it should be possible to use sensors 10having a resonance frequency somewhere in the range from 20 kHz to 35kHz. In order to achieve this, the high pass filter 240 may be designedto having a lower cutoff frequency f_(LC)=20 kHz.

FIG. 6B illustrates an embodiment according to which the digital bandpass filter 240 delivers the filtered signal S_(F) to the digitalrectifier 270, and the rectifier 270 delivers the rectified signal S_(R)directly to a condition analyzer 290 (See FIG. 7 in conjunction withFIG. 6B).

FIG. 7 illustrates an embodiment of the evaluator 230 (See also FIG. 5).The FIG. 7 embodiment of the evaluator 230 includes the conditionanalyser 290 adapted to receive a pre-processed digital signal S_(MDP)indicative of the condition of the machine 6. The condition analyser 290can be controlled to perform a selected condition analysis function 105by means of a selection signal delivered on a control input 300.Examples of condition analysis functions 105 are schematicallyillustrated as boxes in FIG. 7. The selection signal delivered oncontrol input 300 may be generated by means of user interaction with theuser interface 102 (See FIG. 2A).

As mentioned above, the analysis apparatus 14 may include a Peak levelanalysis function F3, 105 (See FIG. 4 & FIG. 7).

According to an embodiment of the invention the Peak level analysisfunction may be performed by the condition analyser 290 in response toactivation via control input 300. In response to the peak level analysisactivation signal, the analyzer 290 will activate a peak level analyzer400 (See FIG. 7), and the digital measurement signal S_(MDP) will bepassed to an input of the peak level analyzer 400.

The peak level analyzer 400 is adapted to monitor the signal for theduration of a peak monitoring time T_(PM) for the purpose ofestablishing a maximum amplitude level A_(PR) indicative of themechanical state of the monitored part, i.e. bearings 7 and/or shaft 8.The maximum amplitude level A_(PR) may also be referred to asrepresentative peak amplitude A_(PR).

As mentioned above, the peak amplitude detected in the measurementsignal may, when the peak amplitude value originates from a mechanicalvibration in the monitored machine, be indicative of the condition ofthe machine. When a bearing assembly is monitored, the peak amplitudevalue may be indicative of the condition of the bearing assembly. Infact, the peak amplitude value may be indicative of Oil film thicknessin a monitored bearing. Hence, the detected peak amplitude may beindicative of separation between the metal surfaces in the rollinginterface. The oil film thickness may depend on lubricant supply and/oron alignment of the shaft. Moreover, the oil film thickness may dependon the load on the shaft, i.e. on the force with which metal surfacesare pressed together, the metal surfaces being e.g. that of a bearingand that of a shaft. The actual detected value of the maximum amplitudelevel may also depend on the mechanical state of the bearing surfaces.

However, the ability to correctly indicate the condition of therotational part based on a detected peak amplitude value requires thatthe detected peak amplitude value really does originate from therotational part. Machines in an industry, such as a e.g. a paper millmay be exerted to mechanical impacts from tools or other machinery,which may cause mechanical vibrations or shock waves in the monitoredmachine. Hence, a peak amplitude level in the digital measurement signalmay be caused by the environment of the machine, in which case theactual highest amplitude value detected in the digital measurementsignal may have nothing to do with the condition of the monitoredmachine part 8. For the purpose of this document, such peak amplitudelevels in the digital measurement signal that do not depend on themechanical state of the monitored part 8 are regarded as noise.Moreover, electrical fields in the environment of the sensor or in thevicinity of conductors of the condition analysis system may interfere togive rise to peak voltage amplitudes in the measuring signal. Such peakvoltage amplitudes may also be regarded as noise.

The inventor realized that there is a particularly high noise level inthe mechanical vibrations of certain machinery, and that such noiselevels hamper the detection of machine damages. Hence, for some types ofmachinery, conventional methods for preventive condition monitoring havefailed to provide sufficiently early and/or reliable warning ofon-coming deteriorating conditions. The inventor concluded that theremay exist a mechanical vibration V_(MD) indicative of a deterioratedcondition in such machinery, but that conventional methods for correctlydetecting such a vibration may hitherto have been inadequate.

The inventor also realized that machines having slowly rotating partswere among the types of machinery for which conventional methods forpreventive condition monitoring have failed to provide sufficientlyreliable warning of on-coming deteriorating conditions.

Having realized that a particularly high noise level in the mechanicalvibrations of certain machinery hampers the detection of machinedamages, the inventor came up with a method for enabling a more reliabledetection of a signal peak amplitude level which is indicative of anincipient damage of a rotational part 8 of the monitored machine 6.

However, tests have indicated that, even in a laboratory environmentwhere there is very little or no noise, the detected peak level for arotational part often varies, i.e. each revolution of a rotational shaftdoes not produce identical peak levels. After careful study of suchamplitude levels the inventor concluded that the amplitude levelsemanating from rotation of a monitored rotational part closely followthe normal distribution, also referred to as the Gaussian distribution;and that it is necessary to record the amplitude levels originating fromplural revolutions of a rotational part in order to detect a relevanttrue peak value which may be used for accurate determination of thecondition of the monitored rotational part.

In this context, it should be noted that the normal distribution is aprobability distribution that describes data that cluster around themean. The graph of the associated probability density function isbell-shaped, with a peak at the mean, and is known as the Gaussianfunction or bell curve.

FIG. 8 is a schematic illustration of a rectified signal S_(R) thatcould be delivered by rectifier 270 (FIG. 6B) to peak analyzer 400 (FIG.7). FIG. 5 in conjunction with FIG. 6B and FIG. 7 provide an overview ofan embodiment of the analysis apparatus. The peak level analysis F3 (SeeFIG. 7 & FIG. 4) is adapted to monitor the signal for the duration of apeak monitoring period T_(PM) for the purpose of establishing a relevantmaximum amplitude level. In the example illustrated in FIG. 8 themonitoring period T_(PM) corresponds to 14 revolutions of the monitoredrotational part. Single revolutions of the monitored rotational part areindicated by reference 405 in FIG. 8.

Accordingly, by defining the monitoring period T_(PM) in terms of anumber of revolutions of the rotational part to be monitored, ratherthan in terms of a certain time period, the quality of the analysis inimproved. More precisely, the inventor realized that when the number ofdetected peak values A_(P) is seen in relation to the amount R ofrevolution of the monitored rotatable part during the measurement,statistical methods may be employed so as to achieve an increasedquality of the resulting peak amplitude value.

The inventor realized that if the distribution of detected peakamplitude values A_(P) resembles the Gaussian distribution it could beconcluded that one revolution of a shaft may result in a different setof peak amplitude values than another revolution of the same shaft.

An embodiment of the method comprises the steps of:

receiving a first digital signal dependent on mechanical vibrationsemanating from rotation of said part;

analysing said first digital signal so as to detect peak amplitudevalues Ap during a finite time period T_(PM), said finite time periodcorresponding to a certain amount R of revolution of said rotatablepart. The certain amount R of revolution should correspond to more thanone revolution of said monitored rotatable part. The method furthercomprises

defining a plurality N_(R) of amplitude ranges R_(A);

sorting said detected peak amplitude values Ap into correspondingamplitude ranges R_(A) so as to reflect occurrence N of detected peakamplitude values Ap within said plurality of amplitude ranges.

FIG. 9 illustrates a histogram resulting from a measurement wherein themeasuring time period T_(PM) corresponded to fourteen (R=14) revolutionsof the monitored rotatable part under laboratory conditions without anynoise, i.e. each one of the illustrated black dots corresponds to onedetected peak amplitude value A_(P). Hence, the “certain amount ofrevolution” is R=14.0 revolutions, and the finite time period T_(PM) wasthe time it took for the monitored part 8 to revolve 14 revolutions. Themonitored part 8 may be a shaft. Hence, according to embodiments of theinvention the measuring time period T_(PM) may depend on the speed ofrotation of the rotatable part so that when the monitored rotationalpart rotates at slower speed the measuring time period T_(PM) will belonger, and when the monitored rotational part rotates at higher speedthe measuring time period T_(PM) will be shorter.

Based on the knowledge that the measurement was made during R=14 fullrevolutions of the monitored part, and assuming that a highest peakamplitude value is detected once per revolution, it can be seen fromFIG. 9 that the top fourteen (14) detected amplitude values do vary abit, the highest amplitude being indicated by reference 410 and the14^(th) highest amplitude range being indicated by reference 420. Hence,from FIG. 9 it may be deduced that the peak amplitude value A_(P)detected during one revolution often differs from the peak amplitudevalue detected during another revolution. In other words, if measurementwere done during a single revolution, then pluralsingle-revolution-measurements on the same shaft would result in ratherlarge variations in the detected peak value.

The Inventor realized that it is desirable to achieve a measurementprocedure which is reliable in the sense that it should providerepeatable results. Hence, when the measurement procedure is repeatedlyperformed on the same rotational part so that plural monitoring periodsT_(PM1), T_(PM2), T_(PM3), T_(PM4), T_(PM5) result in measurementresults in the form of plural representative peak amplitude valuesA_(PR1), A_(PR2), A_(PR3), A_(PR4) being produced in immediate temporalsuccession, then it is desirable that these plural representative peakamplitude values A_(PR1), A_(PR2), A_(PR3), A_(PR4) have substantiallythe same numerical value.

Finite Time Period for Peak Value Detection

By performing numerous test measurements in a laboratory environmentwhere there is very little or no noise, the inventor concluded that itis desirable to monitor a rotating part for the during a finite timeperiod T_(PM) corresponding to several revolutions R in order to detecta true peak amplitude value A_(PT) which is indicative of the mechanicalstate of the monitored part, i.e. bearings 7 and/or shaft 8. In thiscontext the true peak amplitude value A_(PT) is true in the sense thatit truly originates from a mechanical vibration V_(MD) caused by arelative movement between metal surfaces in a monitored part, such ase.g. a bearing ball and an inner ring surface, and not from any noise ordisturbance. In effect the selection of the value for the parameter R isa question which needs careful weighing up, since monitoring during asingle revolution, i.e. R=1, is likely to result in a too low peakamplitude value A_(PT) which therefore may be inadequate for indicatingthe mechanical state of the monitored rotating part. On the other hand,if the rotating part is monitored for an extremely long time, nearingeternity in statistical terms, the detected peak amplitude value A_(PT)will slowly increase to infinity, which in reality means that after anextremely long period of operation a rotating part associated with abearing assembly will break. Accordingly, the inventor concluded that itis necessary to find a balanced value for the parameter R, so as to onthe one hand having a high enough R-value to detect a true peakamplitude value A_(PT) which is indicative of the mechanical state ofthe monitored part, while on the other hand a low enough R-value so asto keep the duration of the measuring time period T_(PM) at a reasonablefinite duration.

Based on numerous test measurements in substantially noise freeconditions, the inventor concluded that it is desirable to monitor arotating part during a finite time period T_(PM) corresponding to acertain amount R of revolution of said rotatable part; said certainamount R of revolution corresponding to at least eight (R=8) revolutionsof said monitored rotatable part in order to actually detect a true peakamplitude value A_(PT) which is indicative of the mechanical state ofthe monitored part. Based on these test measurements, the Inventorconcluded that monitoring the rotating part during a finite time periodT_(PM) corresponding to at least ten (R=10) revolutions of saidmonitored rotatable part renders a more accurate true peak amplitudevalue A_(PT), i.e. a true peak amplitude value Apr which is moreaccurately indicative of the mechanical state of the monitored part.This conclusion is based on tests indicating that a further increase ofthe monitoring time period T_(PM) to a finite duration of more than ten(R=10) revolutions, in an environment free from noise, may lead to adetection of a higher true peak amplitude value A_(PT), but the increasein detected true peak amplitude value A_(PT) is small in relation to theincreased monitoring time period T_(PM).

When measuring and collecting peak amplitude values A_(P) during a timeperiod T_(PM) corresponding to R=14 full revolutions of the monitoredpart, and thereafter organising the peak amplitude values A_(P) in ahistogram, as illustrated in FIG. 9, the peak amplitude values A_(P)sorted into the amplitude level 420 for the 14.th highest detectedamplitude is very stable. It can be seen from the histogram in FIG. 9that four peak amplitudes were detected at that amplitude range 420.Accordingly, a stable measurement value, i.e. repeatedly providingsubstantially the same peak amplitude when performing pluralmeasurements on the same rotating part, may be achieved by focusing onthe R:th highest amplitude, wherein R is a number indicative of thenumber of revolutions performed by the monitored part during the peaklevel monitoring time T_(PM).

An embodiment of the invention therefore includes a method of operatingan apparatus for analysing the condition of a machine having a partrotating with a speed of rotation f_(ROT) comprising the steps of:

receiving a first digital signal S_(MD), S_(R), S_(F) dependent onmechanical vibrations emanating from rotation of said part;

analysing said first digital signal so as to detect peak amplitudevalues Ap during a finite time period T_(Pm), said finite time periodcorresponding to a certain amount R of revolution of said rotatablepart; said certain amount R of revolution corresponding to more than onerevolution of said monitored rotatable part;

sorting said detected peak amplitude values Ap into correspondingamplitude ranges so as to reflect occurrence N of detected peakamplitude values Ap within a plurality N_(R) of amplitude ranges;

estimating a representative peak amplitude value A_(PR) In dependence onsaid sorted peak amplitude values Ap and said certain amount R.

According to an advantageous embodiment the estimation includesselecting the R:th highest amplitude to be said representative peakamplitude value A_(PR).

Reducing or Eliminating Noise

FIG. 10 illustrates a histogram resulting from a measurement wherein thepeak level monitoring time T_(PM) corresponded to fourteen (14)revolutions of the monitored rotatable part. The FIG. 10 histogram isthe result of an experiment wherein two very high amplitude mechanicaldisturbances 430, 440 were generated during the peak level monitoringtime T_(PM) The two signal peaks corresponding to the two very highamplitude mechanical disturbances 430, 440 are also illustrated in FIG.8. It is to be understood that the two high amplitude mechanicaldisturbances 430, 440 were not caused by any damage in the monitoredrotational part. Hence, the two high amplitude mechanical disturbances430, 440 are to be regarded as noise.

Experience and a multitude of measurements have indicated that whenmonitoring a machine having a part rotating with a speed of rotation thehighest peak amplitude value emanating from an incipient damage is avery relevant amplitude value for the purposes of predictivemaintenance.

However, since the highest peak amplitude value does not appear everytime the monitored shaft revolves one full revolution, it will benecessary to monitor a rotatable part for the duration of a timeallowing plural revolutions. Unfortunately, however, in a real lifesituation a longer measuring time often increases the noise level in themeasuring signal. In an industrial environment, such as a paper mill,other machinery in the vicinity of the monitored machine may causemechanical vibrations or shock pulses from time to time, and the longerthe measuring time the greater the risk that such external mechanicalvibrations cause the highest detected peak amplitude levels. For thesereasons the measurement procedure, intended to provide a reliable andrepetitively achievable representative peak amplitude value, needs tosatisfy the opposing requirements of:

on the one hand involving measurement over sufficiently long time tocollect peak amplitude values over plural revolutions of the monitoredrotational part so as to collect a peak amplitude value which isrepresentative of the highest peak amplitude value caused by thecondition of the monitored rotational part, while

on the other hand avoiding the measurement procedure requiring such along time that noise caused by e.g. other machinery in an industrialenvironment corrupts the measurement results.

According to an embodiment of the invention the R:th highest amplitudeis selected to be a representative peak amplitude value A_(PR). Thisembodiment advantageously leads to reduced or eliminated impact of highamplitude noise on the resulting representative peak amplitude valueA_(PR). This advantageous effect is understood by studying and comparingFIGS. 9 and 10. Both of the histograms of FIGS. 9 and 10 illustrate ahistograms resulting from a measurement duration period T_(PM), saidmeasurement duration period T_(PM) corresponding to a certain amountR=14 revolutions of said rotatable part. FIG. 9 illustrates a histogramresulting from a measurement without any noise, whereas FIG. 10illustrates a histogram resulting from another measurement where highamplitude noise was introduced during the measurement. Selection of theR:th highest amplitude as representative peak amplitude value A_(PR)leads to repeatable results, even when exerted to noise. Hence, when themeasurement procedure is repeatedly performed on the same rotationalpart so that plural monitoring periods T_(PM1), T_(PM2), T_(PM3),T_(PM4), T_(PM5) result in measurement results in the form of pluralrepresentative peak amplitude values A_(PR1), A_(PR2), A_(PR3), A_(PR4)being produced in immediate temporal succession, these pluralrepresentative peak amplitude values A_(PR1), A_(PR2), A_(PR3), A_(PR4)have substantially the same numerical value, when the R:th highestamplitude is selected to be a representative peak amplitude value A_(PR)and the measurement duration periods T_(PM1), T_(PM2), T_(PM3), T_(PM4),T_(PM5) correspond to R revolutions of said rotatable part. Startingfrom the right hand side and identifying 14:th highest amplitude value,leads to substantially the same amplitude level, both in the case ofFIG. 9 and FIG. 10. Hence, the amplitude level of the R:th highestamplitude value may advantageously be selected representative peakamplitude value A_(PR), according to an embodiment.

However, the nature of the Gaussian function or bell curve is such thatthe frequency of low amplitude values actually can tell us somethingabout the amplitude of the not-so-frequent highest peak amplitudevalues.

According to an aspect of the Invention, the method includes estimatinga representative peak amplitude value (A_(PR)) independence on saidsorted peak amplitude values (Ap) and said certain amount (R).

According to an embodiment the estimation step includes the creation ofan accumulated histogram.

Setting Up an Analysis Apparatus for Performing Peak Level Analysis

FIG. 11A is a flow chart illustrating an embodiment of a method ofoperating the apparatus 14 so as to set it up for performing peak levelcondition analysis. The method according to FIG. 11A may be performedwhen an embodiment of the analysis function F3 (See FIG. 4 & FIG. 7) isrun on the processor 50 (See FIG. 2A).

In a step S10 a parameter value R is set, and in another optional stepS20 a parameter n may be set. According to an embodiment the parametervalues R and n, respectively, may be set in connection with themanufacturing or in connection with delivery of the measurementapparatus 14. Accordingly the parameter values R and n may be preset bythe manufacturer of apparatus 14, and these values may be stored in thenon-volatile memory 52 or in the non-volatile memory 60 (See FIG. 2A).

Alternatively, the parameter values R and n may be set by the user ofthe apparatus 14 prior to performing a measurement session. Theparameter values R and n may be set by the user by means of the userinterface 102, 107 described in connection with FIG. 2A.

A Method of Measurement and Data Collection

FIG. 11B is a flow chart illustrating an embodiment of a method ofoperating the apparatus 14 so as to perform peak level conditionanalysis. The method according to FIG. 11B may be performed when anembodiment of the analysis function F3 (See FIG. 4 & FIG. 7) is run onthe processor 50 (See FIG. 2A).

In a step S50 a current speed value f_(ROT) is read, and stored in adata memory 52. When the part 8 to be monitored is rotating with aconstant speed of rotation, the speed value f_(ROT) may be entered by auser via the user interface 102 (FIG. 2A). When the rotational speedf_(ROT) of the monitored part is variable, a speed detector 450 (SeeFIG. 1 & FIG. 5) may be provided to deliver a signal indicative of thespeed of rotation f_(ROT) of the shaft 8. The speed of rotation f_(ROT)of the shaft 8 may be provided in terms of revolutions per second, rps,i.e. Hertz (Hz) to an input 460 of means 180 for digital signalprocessing (See FIG. 5) so that it can be used by the processor 50 (SeeFIG. 2A) when running the program to execute the peak amplitude analysisfunction.

In step S60 additional preparations for the measurement session step S70are performed.

The preparations of step S60 may include preparing a suitable table 470for data to be collected. FIG. 13B is a schematic illustration of pluralmemory positions arranged as a table 470, and suitable for storage ofdata to be collected. The table 470 may be stored in the memory 52 (FIG.2A) or in a memory internal to the processor 50.

FIG. 13A illustrates a histogram having plural amplitude bins 500,individually referred to by references r1 to r750, each amplitude bin r1. . . r750 representing an amplitude level A_(r). Although FIG. 13 shows750 (seven hundred and fifty) amplitude bins, that is just an examplevalue. The number of amplitude bins may be set to a suitable number instep S60 (FIG. 11B) by the user, via user interface 102 (FIG. 2A). FIG.13A is comparable with FIG. 10, both figures illustrating a number ofamplitude bins along one axis 480, and occurrence of detected peakamplitude values along another axis 490. However, in the illustration ofFIG. 13A no values have been plotted in the histogram. The amplitudeaxis 480 may have a certain resolution, which may also be settable bythe user, via the user interface 102. Alternatively the resolution ofthe amplitude axis 480 may be preset. According to an embodiment theresolution of the amplitude axis 480 may be set to 0.2 dB, and theamplitudes to be recorded may span from a lowest amplitude of A_(r1)=−50dB to a highest amplitude value A_(r750)=+100 dB.

With reference to FIG. 13B, the Illustrated table is a representation ofthe histogram shown in FIG. 13A, having amplitude bins 500, individuallyreferred to by references r1 to r750, each amplitude bin r1 . . . r750representing an amplitude level A_(r). The table 470 also includesmemory positions 510 for amplitude values Ar, and memory positions 520for variables N_(r), reflecting the occurrence.

Bin r1 is associated with an amplitude value A_(r1) and with a memoryposition for a variable N_(r1) for storing a value indicating how manytimes the amplitude Ar1 has been detected.

In step S60 (FIG. 11B), before the start of a measuring session S70, allthe occurrence variables N_(r1) to N_(r750) may be set to zero (0).Thereafter the measuring session S70 may begin.

The measuring session s70 may include receiving a first digital signalS_(R), S_(MDP) dependent on mechanical vibrations emanating fromrotation of said part (See FIG. 6B & FIG. 7); and

analysing said first digital signal S_(R), S_(MDP) so as to detect peakamplitude values Ap during a finite time period T_(Pm), said finite timeperiod corresponding to a certain amount R of revolution of saidrotatable part 8; said certain amount R of revolution corresponding tomore than one revolution of said monitored rotatable part; and sortingsaid detected peak amplitude values Ap into corresponding amplituderanges 500 so as to reflect occurrence N of detected peak amplitudevalues Ap within said plurality of amplitude ranges 500 (See FIG. 13B).

The duration of the measurement session is controlled in dependence ofthe amount of revolution of the rotating part, so that the rotating partrotates at least R revolutions, as mentioned above. Step S80 in FIG. 11Brepresents the step of controlling the duration of the finite timeperiod T_(Pm) accordingly. A revolution counter may be provided tomonitor the signal f_(ROT) so as to ascertain that the measurementsession continues for the duration of the finite time period T_(Pm),corresponding to the certain amount R of revolution of said rotatablepart 8. Alternatively, the detector 450 may generate a signal indicativeof the amount of revolution, and the duration of measurement may becontrolled solely in dependence on the amount of revolution of therotatable part 8, irrespective of time. Alternatively, the durationT_(Pm) of the measurement session is controlled in dependence of timeinformation provided by the clock 190 (FIG. 5) in conjunction with speedof rotation information f_(ROT) delivered by detector 450 so that theduration T_(Pm) is adapted to ensure that the monitoring is performedfor the desired amount of rotation n*R. In this connection it is notedthat R is a positive number larger than one, and n is a positive numberequal to one (1) or larger than one (1). The parameter R may be anInteger, but it may alternatively be a decimal number. The parameter nmay be an integer, but it may alternatively be a decimal number. In theexample shown in FIG. 8 above, parameter R=14 and parameter n=1.

In a step S90 (FIG. 11B) a representative peak amplitude value A_(PR) isestablished on the basis of the peak amplitude values Ap collected inthe measurement session S70.

FIG. 12A is a flow chart illustrating an embodiment of a method ofperforming step S70 so as to perform the peak level measurement session.

In a step S100 a digital signal S_(R), S_(MDP) dependent on mechanicalvibrations is received by peak level analyzer 400 (See FIG. 7). When asignal peak is detected (Step S110), the peak amplitude value of thedetected peak is measured (Step S120), and a corresponding amplituderange also referred to as amplitude range bin, is identified in stepS130 (See FIG. 12A in conjunction with FIG. 13B).

In a step S140 the corresponding occurrence counter value Nri isincreased by one unit so as to reflect detection of a peak in thatamplitude range bin r_(i).

Thereafter step S80 In FIG. 11B is performed so as to determine whetherthe measuring session is complete or should continue. If is to continue,then steps S100 to S140 are repeated, i.e. step S70 In FIG. 11 isperformed again.

When step S80 determines that the measurement session is complete, arepresentative peak amplitude value A_(PR) is established (S90) on thebasis of the peak amplitude values Ap collected in the measurementsession S70, as mentioned above.

According to an embodiment, the representative peak amplitude valueA_(PR) is compared with a reference value such that the comparison isindicative of the condition of the monitored part. The reference valuemay be a preset value corresponding to the monitored part. According toan embodiment, the reference value may be a representative peakamplitude value A_(PR) which was established by measurement on the samethe monitored part at an earlier time, e.g. when the part was new orfreshly renovated. According to an embodiment the above describedfunctions F7=storage of condition data in a writeable informationcarrier on said machine, and/or F8=storage of condition data in awriteable information carrier 52 in said apparatus, and/or F12=Retrievalof condition data from a writeable information carrier 58 on saidmachine and/or F13=Performing Peak level analysis F3 and performingfunction F12 “Retrieval of condition data from a writeable informationcarrier 58 on said machine” so as to enable a comparison or trendingbased on current Peak level data and historical Peak level data, areemployed.

Establishing Further Improved Representative Peak Value and NoiseRejection

Whereas the measurement results as illustrated in FIG. 9 reflect ahighest peak amplitude 410 detected during R=14 revolutions undersubstantially noise free conditions, the highest peak 430 in themeasurement session illustrated in FIG. 10, detected during R=14revolutions, was generated in response to a disturbance, i.e. itreflects noise, and as such the peak 430 does not carry any informationabout the condition of the rotating part 8. Accordingly, it is desirableto obtain a representative peak amplitude value A_(PR) which is based onsignal values reflecting measurement values delivered by the sensor 10in dependence on vibrations emanating from the shaft and/or bearing whenthe shaft rotates. In particular when it comes to measurement on slowlyrotating parts, which inherently requires a longer measuring periodT_(PM) when measurement is to be performed over a certain predeterminedamount of revolution R, the amount of noise may also be increased due tothe longer duration of the measuring session required because of theslower rotational speed. Hence, there exists a need for a sturdymeasurement method capable of rejecting noise.

In a wind turbine application the shaft whose bearing is analyzed mayrotate at a speed of less than 120 revolutions per minute, i.e. theshaft rotational frequency f_(ROT) is less than 2 revolutions per second(rps). Sometimes such a shaft to be analyzed rotates at a speed of lessthan 50 revolutions per minute (rpm), i.e. a shaft rotational frequencyf_(ROT) of less than 0.83 rps. In fact the speed of rotation maytypically be less than 15 rpm. Whereas a shaft having a rotational speedof 1715 rpm, as discussed in the above mentioned book, produces 500revolutions in just 17.5 seconds; a shaft rotating at 50 revolutions perminute takes ten minutes to produce 500 revolutions. Certain large windpower stations have shafts that may typically rotate at 12 RPM=0.2 rps.At 12 rpm it takes more than four minutes to complete fifty revolutions,and accordingly the risk for impact noise occurring during themeasurement is a lot higher when the peak level analysis is to beperformed on a rotating part having such a low rotational speed.Similarly certain machine parts in paper mills also rotate at a speed ofless than 50 rpm.

As mentioned above, the inventor concluded that it is desirable tomonitor a rotating part during a finite time period T_(PM) correspondingto a certain amount R of revolution of said rotatable part; said certainamount R of revolution corresponding to plural revolutions of saidmonitored rotatable part in order to actually detect a peak amplitudevalue A_(PT) which is indicative of the mechanical state of themonitored part. However, the inventor concluded that it is preferable tomonitor a rotating part during a finite time period T_(PM) correspondingto a certain amount R of revolution of said rotatable part; said certainamount R of revolution corresponding to at least eight (R=8) revolutionsof said monitored rotatable part in order to actually detect a true peakamplitude value A_(PT) which is indicative of the mechanical state ofthe monitored part. This conclusion was based on numerous testmeasurements in substantially noise free conditions. Hence, monitoring arotating part during a finite time period T_(PM) corresponding to atleast n*R revolutions, wherein n is a number having a numerical value ofat least two and R has a numerical value of at least 8, and selectingthe n:th highest detected peak amplitude as a representative peakamplitude value A_(PR), will deliver a measured peak amplitude valueA_(PR) which statistically occurs once in R revolutions, while rejectingthe n−1 highest peak values as potential noise peaks. Accordingly, thisembodiment of the Invention renders a peak amplitude value A_(PR) whichis very accurately indicative of the mechanical state of the monitoredpart.

As mentioned above, the inventor also concluded, based on the testmeasurements, that monitoring the rotating part during a finite timeperiod T_(PM) corresponding to at least ten revolutions (R=10) of saidmonitored rotatable part may render an even more accurate true peakamplitude value A_(PT), i.e. a true peak amplitude value A_(PT) which ismore accurately indicative of the mechanical state of the monitoredpart. Moreover, the inventor concluded that the tests indicate that afurther increase of the monitoring time period T_(PM) to a finiteduration of more than ten revolutions (R>10), in an environment freefrom noise, may lead to a detection of a higher true peak amplitudevalue A_(PT), but the increase in detected true peak amplitude valueA_(PT) is small in relation to the increased monitoring time periodT_(PM).

Accordingly, the Inventor concluded that a problem to be solved is: Howto identify a peak amplitude value which statistically occurs once in Rrevolutions, while satisfying the conflicting requirements of obtainingas accurate as possible a measured peak amplitude value and whileminimizing the measuring duration and achieving rejection of peaks thatare due to noise.

FIG. 14A is a flow chart illustrating an embodiment of a method forestablishing a representative peak amplitude value A_(PR) on the basisof the peak amplitude values Ap collected in the measurement session S70(See FIG. 11A). The method of the FIG. 14A embodiment illustrates amanner by which high amplitude noise may be rejected. Accordingly themethod according to FIG. 14A may advantageously be employed for peaklevel analysis of rotatable parts having a speed of less than 50 rpm.

In a step S150 data relevant for the analysis is read. This includes thevalue of the parameter R, used in the measuring session S70, and thevalue of the parameter n. It may also include the peak value measurementdata in histogram format, as illustrated in FIG. 13A, 13B or 13C. Thepeak value measurement data to be analyzed may be the data collected asdescribed above, e.g. in connection with steps S70 & SS0 above and/or asdescribed in connection with FIG. 12A or 12B.

In step S160, identify the top n:th highest detected peak amplitudevalue. Referring to FIG. 13B, and assuming data is sorted so that thehighest amplitude bin is at the right hand side of the FIG. 13B table(i.e. amplitude A_(r750), associated with bin r₇₅₀, represents thehighest detectable amplitude value), this means beginning withoccurrence N_(r750), moving left and adding occurrence values N_(ri)until the sum equals n. Having found the n:th highest detectedamplitude, the subsequent step S170 includes identifying the amplitudebin r_(i) representing the n:th highest detected peak amplitude valueand the corresponding amplitude value A_(ri).

In the subsequent step S180, select the identified amplitude valueA_(ri) to be an estimate of the representative peak amplitude A_(PR):

A _(PR) :=A _(ri)

Accordingly, an embodiment of the invention includes a method ofoperating an apparatus for analysing the condition of a machine having apart rotating with a speed of rotation f_(ROT), comprising the steps of:

receiving a first digital signal S_(MD), S_(R), S_(F) dependent onmechanical vibrations emanating from rotation of said part;

analysing said first digital signal so as to detect peak amplitudevalues Ap during a finite time period T_(Pm), said finite time periodcorresponding to a certain amount of revolution of said rotatable part;said certain amount of revolution corresponding to more than onerevolution of said monitored rotatable part;

sorting each said detected peak amplitude value Ap into a correspondingamplitude bin 500, r₁-r₇₅₀ (See FIGS. 13B and 13C) so as to reflectoccurrence N of detected peak amplitude values Ap within a pluralityN_(R) of amplitude ranges;

estimating a representative peak amplitude value A_(PR) in dependence onsaid sorted peak amplitude values Ap and said certain amount ofrevolution; wherein

said certain amount of revolution includes at least n*R revolutions,wherein

n is a number having a numerical value of at least two and R correspondsto several revolutions, and wherein

the estimation step includes selecting the n:th highest detected peakamplitude as a representative peak amplitude value A_(PR).

This solution advantageously rejects the n−1 highest amplitude peakvalues as noise, and delivers the n:th largest amplitude peak value as arepresentative peak amplitude value A_(PR). According to this embodimentthe duration of a measurement session, expressed in number ofrevolutions, will be n*R, and the number of rejected noise peak valuesis n−1.

According to an embodiment, n is a number having a numerical value of atleast two and R has a numerical value of at least 8, renderingmeasurement and collection of peak amplitude values during at least*R=2*8=16 revolutions of the monitored part (Steps S70 and S80 in FIG.11B).

According to a preferred embodiment, referring to steps S10 and S20 inFIG. 11A, the parameter R is set to at least 10, and parameter n is setto 5, rendering measurement and collection of peak amplitude valuesduring n*R=510=50 revolutions of the monitored part (Steps S70 and S80in FIG. 11B).

If a true peak value is generated at least once in R revolutions, andthere is also some high amplitude noise in the form of false peakvalues, then according to this embodiment the four highest peak valuesmay be rejected and the method will still identify a true peak value inthe form of the n:th largest detected peak value, i.e. the fifth largestdetected peak value. Accordingly, assuming that the amount of highamplitude disturbance results in at the most four of the top five peakvalues, this embodiment delivers the amplitude of the 5:th largest peakvalue as a representative peak amplitude value A_(PR).

According to preferred embodiments of the invention the parameter R maytake values of 8 or higher, and the parameter n may have values of 2 orhigher. According to these embodiments the duration of a measurementsession, expressed in number of revolutions, will be n*R, and the numberof rejected noise peak values is n−1.

The below Table 1 illustrates a few examples of combinations ofparameter settings for R and n, together with resulting duration ofmeasuring session and the corresponding capability of noise rejection.

TABLE 1 Duration of Number of measurement session rejected R n(revolutions) noise peaks 8 5 40 4 9 5 45 4 10 5 50 4 10 6 60 5 10 7 706 10 8 80 7 10 9 90 8 10 10 100 9 10 11 110 10 10 12 120 11 10 13 130 1210 14 140 13 9 6 54 5 9 7 63 6 9 8 72 7 9 9 81 8 9 10 90 9 9 11 99 10 912 108 11

However, the inventor also concluded that since the distribution of truepeak amplitude values emanating from rotation of a monitored rotationalpart closely follow the normal distribution, it may be possible toestimate a peak amplitude value which statistically occurs seldom, onthe basis of detected peak amplitude values which occur more frequently.On the basis of this realization, the inventor proceeded to develop afurther advantageous manner of estimating a representative peakamplitude value A_(PR) in dependence on the sorted peak amplitude valuesAp and the amount R of rotation of the monitored part, as discussedbelow in connection with FIG. 14B.

Yet a Further Improved Representative Peak Value and Noise Rejection

FIG. 14B is a flow chart illustrating yet an embodiment of a method forestimating a representative peak amplitude value A_(PR) on the basis ofthe peak amplitude values Ap collected in the measurement session S70.The method of FIG. 14B may be an embodiment of step S90 of FIG. 11B.

In a step S200 a parameter g is set to a value (n*R)/q₁:

g:=(n*R)/q ₁

The parameter q₁ may have a numerical value 1 or more than 1. Accordingto embodiments of the invention parameter q₁ is preset to a value ofbetween one (1) and three (3).

In a step S210, an amplitude range r_(g) (See FIG. 13) holding the g:thlargest detected peak amplitude value is identified.

In a step S220 a parameter h is set to a value (n*R)/q₂:

h=n*R/q ₂

According to embodiments of the invention, the parameter ‘h is preset toa value of between two (2) and five (5). According to an embodiment theparameter q₂ may have a numerical value four (4). The value of parameterq₂ is always larger than the value of parameter q₁:

q ₂ >q ₁

In a step S230, an amplitude range r_(h) (See FIG. 13) holding the h:thlargest detected peak amplitude value is identified.

In a step S240, an estimate of a representative peak amplitude valueA_(PR) is achieved on the basis of the values (r_(g), g) and (r_(h), h).This will be explained in further detail below in connection with FIG.15A.

Setting parameters n=5, R=10, and q₁=1 in step S200 renders g=50. Hencethe measuring session includes 50 revolutions (since n*R=50), andsetting g=50 implies that we identify the position in the histogramwhere the 50:th largest detected pulse is stored. Hence, with referencee.g. to the histogram of FIG. 13, we are identifying the position wherepulse amplitudes that occur with a frequency of once per revolution willbe reflected. Differently worded, it to be understood that, since thedistribution of true peak amplitude values emanating from rotation of amonitored rotational part closely follows the normal distribution, thensorting the detected peak amplitude values into amplitude bins r, 500(See FIGS. 13A, 13B and/or 13C), and then identifying the amplitude binr, 500 holding the g:th largest detected peak amplitude value, rendersidentification of an amplitude value r_(g) which has occurred 50 times(since g=50) during 50 revolutions (since n*R=50), i.e. statistically apeak amplitude of at least the peak amplitude value r_(g) has occurredg/(n*R) times/revolution, which is once per revolution when g=50 andn*R=50. In other words, the average occurrence frequency f_(ag),expressed as occurrences per revolution, of an amplitude having a valueof r_(g) or higher is:

f _(ag) =g/(n*R)occurrences/revolution

Similarly, setting the parameter q₂=4 in step S200 rendersh=n*R/q₂=12.5. Hence the measuring session includes 50 revolutions(since n*R=50), and setting h=12 implies that we identify the positionin the histogram where the 12:th largest detected pulse is stored. Hencewe are identifying the position in the histogram of FIG. 13 where pulsesthat occur with a frequency of once every four revolutions will bereflected. In other words, the average occurrence frequency f_(ah),expressed as occurrences per revolution, of an amplitude having a valueof r_(h) or higher is:

f _(ah) =h/(n*R)occurrences/revolution

When parameters n=5, R=10, and h=n*R/q₂=12.5, renders

f_(ah)=h/(n*R)=% occurrences/revolution, i.e. one occurrence every fourrevolutions

As mentioned above, the nature of the Gaussian function or bell curve issuch that the amplitude and frequency of low amplitude values actuallycan tell us something about the amplitude of the not-so-frequent highestpeak amplitude values. This is true even if only a part of theamplitude-frequency plot (See FIG. 9, 10, 13A, 13B, 13C) resembles theGaussian function or bell curve, such as e.g. if the high amplitude partof the plot of detected peak values follows the Gaussian function orbell curve.

Since at least the high amplitude part of the distribution of true peakamplitude values emanating from rotation of a monitored rotational partclosely follow the normal distribution, these two positions in thehistogram may be used for estimating a peak amplitude value whichstatistically occurs more seldom. As mentioned above (See heading“Finite Time Period for Peak Value Detection” above), the representativepeak amplitude value A_(PR) may be an amplitude which statisticallyoccurs once every R revolutions. Accordingly, having set parameter R tovalue 10, the method includes estimating the amplitude of a peak valueoccurring once in ten revolutions, based on the observation ofoccurrence frequency and amplitude of peaks occurring once perrevolution and once in four revolutions. Advantageously, this methodenables the rejection of 11 high amplitude false peak values while stillenabling the estimation of an accurate representative peak amplitudevalue A_(PR), when parameters g and h, respectively, are set asmentioned above, i.e. g=50 and h=12.5. Moreover, it is to be noted thatthis method enables the rejection of 11 high amplitude false peak valueswhile reducing the required measurement session duration T_(PM) tomerely the duration of 50 revolutions. This is since n*R=5*10=50. Thiseffect is advantageously achieved since parameters q1 and q2 areselected such that the two parameters g & h are selected to valuesrepresenting relatively high frequency of occurrence of peak amplitudevalues, and the amplitudes of the high occurrence frequency values areused for estimating a peak amplitude value A_(PR) which statisticallyoccurs more seldom, such as once in R revolutions. Hence, arepresentative peak amplitude level A_(PR) having an average occurrenceof once every R:th revolution can be estimated on the basis of the peakamplitude levels having an average occurrence of once every g:threvolution and the peak amplitude levels having an average occurrence ofonce every h:th revolution. The number of rejected noise peaks PNR isone less than the truncated value of h:

P _(NP)=TRUNC(h)−1

Accordingly the embodiment according to FIG. 14B enables substantiallythe same accuracy in estimation of representative peak amplitude valueA_(PR) based on measurement during 50 revolutions as the methodaccording to the FIG. 14A embodiment does based on measurement during120 revolutions (compare with Table 1 above). The below Table 2illustrates a few examples of combinations of parameter settings for Rand n, together with resulting duration of measuring session and thecorresponding capability of noise rejection.

TABLE 2 Duration of Parameter Number of measurement session Parameter h= rejected R n (revolutions) q2 (n*R)/q2 noise peaks 8 5 40 4 10 9 9 545 4 11.25 10 10 5 50 4 12.5 11 10 6 60 4 15 14 10 7 70 4 17.5 16 10 880 4 20 19 10 9 90 4 22.5 21 10 10 100 4 25 24 10 11 110 4 27.5 26 10 12120 4 30 29 10 13 130 4 32.5 31 10 14 140 4 35 34 9 6 54 4 13.5 12 9 763 4 15.75 14 9 8 72 4 18 17 9 9 81 4 20.25 19 9 10 90 4 22.5 21 9 11 994 24.75 23 9 12 108 4 27 26

According to an embodiment of the invention, the estimation may beperformed by producing an accumulated histogram table reflecting allamplitudes detected in a measurement session and their frequency ofoccurrence. FIG. 13C is an illustration of such a cumulative histogramtable 530 corresponding to the histogram table of FIG. 13B. Thecumulative histogram table of FIG. 13C includes the same number ofamplitude range bins as the FIG. 13B table. In the cumulative histogramthe occurrence N′ is reflected as the number of occurrences of detectedpeaks having an amplitude higher than the amplitude A_(r)′ of associatedamplitude bin r. This advantageously provides for a smoother curve whenthe cumulative histogram is plotted. Whereas the ‘ordinary’ histogramreflecting a limited number of observations will reflect a lack ofobservations Nat an amplitude bin as a notch or dent at that bin, thecumulative histogram will provide a smoother curve, which makes is moresuitable for use in estimating occurrence at one amplitude level basedon the observation of occurrences at other amplitude levels.

According to an embodiment of the invention, the amplitude levels arereflected as logarithmic values, and also the cumulative occurrence isreflected by the logarithmic value of the cumulative occurrence.

FIG. 15A is an illustration reflecting the principle of a cumulativehistogram resulting from a measurement, and corresponding to the tableof FIG. 13C. Although a cumulative histogram using real detected valuesmay take a different shape from that shown in FIG. 15A, the principle ofestimating the representative peak amplitude A_(PR), reflecting theamplitude level which occurs once every R:th revolution, is illustratedin FIG. 15A.

One axis 542 of the cumulative histogram reflects occurrence, and theother axis 544 reflects amplitude. When n=5, R=10, q1=1 then g=50representing 50 occurrences, which also corresponds to one occurrenceper revolution. One occurrence per revolution may be written: “1/1”.Accordingly, the axis 542 of the cumulative histogram reflectingoccurrence may reflect g as “1/1”. Similarly h may reflect an occurrenceof one in four also expressed as “1/4”, and when R=10, then R mayreflect an occurrence of one in ten also expressed as “1/10” (See FIG.15A).

Parameter values rg, g and rh, h, may be determined in the mannerdescribed above in connection with FIG. 14B. Parameter values rg, greflects a point 550 in the cumulative histogram indicating peaks thatoccur once per revolution. Parameter values rh, h reflects a point 560in the cumulative histogram indicating peaks that occur once per fourrevolutions. The inventor realized that in the logarithmic cumulativehistogram this part of the normal distribution curve closely resembles astraight line, making it possible to draw a straight line 570 throughpoints 550 and 560. When that line 570 is extended it will cross a line580 representing the R-occurrence at a point 590. The amplitude value ofpoint 590 represents the amplitude level A_(PR) which occurs once everyR:th revolution. Hence, a representative peak amplitude level A_(PR)having an average occurrence of once every R:th revolution can beestimated on the basis of the peak amplitude levels having an averageoccurrence of once every g:th revolution and the peak amplitude levelshaving an average occurrence of once every h:th revolution. FIG. 15Aillustrates this, with example values g=1, h=4 and R=10.

On the basis of testing, the inventor established that the parameter q1should advantageously have a value of no less than one (1), sinceselecting the parameter q1 to less than one may lead to poor results inthe estimation process because a cumulative histogram reflecting abearing assembly having an outer ring damage deviates comparatively morefrom a straight line, thereby rendering a larger error in theestimation.

Accordingly, an embodiment of the invention includes a method ofoperating an apparatus for analysing the condition of a machine having apart rotating with a speed of rotation f_(ROT) comprising the steps of:

receiving a first digital signal S_(MD), S_(R), S_(F) dependent onmechanical vibrations emanating from rotation of said part;

detecting peak amplitude values Ap occurring in said first digitalsignal during a finite time period T_(Pm), said finite time periodcorresponding to a certain amount of revolution of said rotatable part;said certain amount of revolution corresponding to more than onerevolution of said monitored rotatable part;

sorting each said detected peak amplitude value Ap into a correspondingamplitude bin 500, r₁-r₇₅₀ (See FIGS. 13B and 13C) so as to reflectoccurrence N of detected peak amplitude values Ap within a plurality Nriof amplitude ranges;

estimating a representative peak amplitude value A_(PR) in dependence onsaid sorted peak amplitude values Ap and said certain amount ofrevolution; wherein

-   -   said certain amount of revolution includes at least R        revolutions, and wherein    -   the estimation step includes estimating an amplitude value        A_(PR), which occurs on average substantially once per R        revolutions, in dependence of detected amplitude levels A_(p)        which on average occur more frequently than once per R        revolutions.

According to an embodiment of the above solution, said certain amount ofrevolution includes at least n*R revolutions, wherein

n is a number having a numerical value of at least 1 and R has anumerical value of at least 8.

According to another embodiment, n is a number having a numerical valueof at least 2 and R has a numerical value of at least 8.

According to an embodiment there is provided a method of operating anapparatus for analysing the condition of a machine having a partrotating with a speed of rotation f_(ROT) comprising the steps of:

receiving a first digital signal S_(MD), S_(R), S_(F) dependent onmechanical vibrations emanating from rotation of said part;

detecting peak amplitude values Ap occurring in said first digitalsignal during a finite time period T_(Pm), said finite time periodcorresponding to a certain amount of revolution of said rotatable part;said certain amount of revolution corresponding to more than onerevolution of said monitored rotatable part;

sorting each said detected peak amplitude value Ap into a correspondingamplitude bin 500, r₁-r₇₅₀ (See FIGS. 13B and 13C) so as to reflectoccurrence N of detected peak amplitude values Ap within a pluralityN_(R) of amplitude ranges;

estimating a representative peak amplitude value A_(PR) in dependence onsaid sorted peak amplitude values Ap and said certain amount ofrevolution; wherein

said certain amount of revolution includes at least n*R revolutions,wherein

-   -   n is a number having a numerical value of at least two and R has        a numerical value of at least 8, and wherein

the estimation step includes estimating an amplitude value A_(PR) whichoccurs on average substantially once per R revolutions in dependence ofdetected amplitude levels A_(p) which occur once every h:th revolution,wherein h has a numerical value of less than n*R. According to an aspectof this solution, the estimation step includes estimating an amplitudevalue A_(PR) which occurs on average substantially once per Rrevolutions in dependence of detected amplitude levels A_(P) which occuronce every h:th revolution, wherein h has a numerical value of less thann*R and in dependence of detected amplitude levels A_(P) which occuronce every g:th revolution, wherein g has a numerical value of less thanh.

An embodiment of the invention includes a method of operating anapparatus for analysing the condition of a machine having a partrotating with a speed of rotation f_(ROT) comprising the steps of:

receiving a first digital signal S_(MD), S_(R), S_(F) dependent onmechanical vibrations emanating from rotation of said part;

detecting peak amplitude values Ap occurring in said first digitalsignal during a finite time period T_(Pm), said finite time periodcorresponding to a certain amount of revolution of said rotatable part;said certain amount of revolution corresponding to more than onerevolution of said monitored rotatable part;

sorting each said detected peak amplitude value Ap into a correspondingamplitude bin 500, r₁-r₇₅₀ (See FIGS. 13B and 13C) so as to reflectoccurrence N of detected peak amplitude values Ap within a plurality Nriof amplitude ranges;

estimating a representative peak amplitude value A_(PR) in dependence onsaid sorted peak amplitude values Ap and said certain amount ofrevolution; wherein

said certain amount of revolution includes at least n*R revolutions, andwherein

the estimation step includes estimating an amplitude value A_(PR), whichoccurs on average substantially once per R revolutions, in dependence ofdetected amplitude levels A_(P) which on average occur more frequentlythan once per R revolutions.

This solution advantageously provides repeatable results since thedelivered amplitude level A_(PR) is based on measured values having ahigh occurrence frequency. Moreover, the delivered amplitude levelA_(PR) is substantially the highest measurable amplitude leveldetectable from a rotating machine part during a finite time periodT_(Pm), as discussed above and as shown by tests performed by theinventor.

Noise Echo Suppression

Moreover, the inventor realized that impact noise in industrialenvironments, which may be caused by an item hitting the body of themachine having a monitored rotating part 8, may cause shock waves whichtravel back and forth, echoing in the body of the machine. Accordingly,such echoing shock waves may be picked up by the sensor 10 (FIG. 1, 2A,5) and reflected in the resulting signal S_(R), S_(MDP) (FIG. 6B, 7) asa burst of amplitude peaks.

Hence, such a burst of amplitude peaks may unfortunately causecorruption of a peak level analysis, unless the impact of such burstscan be reduced or eliminated.

FIG. 12B is a flow chart illustrating an embodiment of a method ofperforming step S70 (FIG. 11B) so as to perform the peak levelmeasurement session and additionally addressing the impact of bursts ofnoise amplitude peaks.

Step S300 of the method embodiment illustrated in FIG. 12B may beperformed after step S60, as described in connection with FIG. 11Babove. In step S300 the peak level analyzer reads the current rotationalspeed f_(ROT) which may be delivered from the speed detector 450, asdescribed above (See FIG. 5). The reading of a real time value of therotational speed f_(ROT) advantageously enables this method to beperformed also when the rotational part to be analysed rotates with avariable speed of rotation.

In a step S310 an echo suppression period T_(es), is calculated. Theecho suppression period T_(es) is set to:

T _(es):=1/(e*f _(ROT))

Wherein, according to an embodiment, e is a factor having a value equalto ten or less than ten:

e<=10

An effect of the echo suppression method is to reduce the number of peakvalues per revolution of the monitored part 8 to a maximum of e peaksper revolution. Accordingly, selecting e=10 renders a maximum deliveryof 10 peaks per revolution. Differently worded the echo suppressionperiod T_(es) will have a duration corresponding to the duration of onetenth revolution, when e=10. The factor e may be set to another othervalue, such as e.g. 8 or 12.

In a step S320 the measurement signal S_(MDP), S_(R) to be analyzed isreceived, and in a step S330 the amplitude of the received signal S_(R)is analyzed so as to detect any received peak values.

In a step S340 any detected peak values A_(p) are delivered at afrequency of f_(es) or less, wherein each delivered peak amplitude valuereflects the highest detected amplitude during the echo suppressionperiod T_(es). This is done so that there may be longer time than oneecho suppression period T_(es) between two consecutively deliveredoutput values from the echo suppresser, but the period between twoconsecutively delivered output values from the echo suppresser willnever be shorter than the echo suppression period T_(es).

In a subsequent step S350, the peak values A_(P) delivered by the echosuppresser are received by a log generator. The log generator calculatesthe logarithm of the peak value A_(p) in real time.

In a step S360 the amplitude bin corresponding to the relevant peakvalue A_(P) is identified in a histogram table 470 and/or 530 (Seehistogram table 470 and cumulative histogram table 530 in FIGS. 13B and13C, respectively), and in a step S370 the corresponding occurrencecounter value N_(ri), N_(ri)′ is increased by one unit.

FIG. 16 is a schematic block diagram of an embodiment of the analysisapparatus 14. A sensor unit 10 is adapted to generate an analogue signalS_(EA) in response to vibrations, as described above in this document.The sensor unit 10 may be a vibration sensor as discussed in connectionwith FIG. 2B above. Alternatively, the sensor unit 10 may be a resonantShock Pulse Measurement sensor 10 having a mechanical resonancefrequency f_(RM), as discussed in connection with FIG. 2B above. Thismechanical resonance feature of the Shock Pulse Measurement sensoradvantageously renders repeatable measurement results in that the outputsignal from a Shock Pulse Measurement sensor has a stable resonancefrequency substantially independent of the physical path between theshock pulse signal source and the shock pulse sensor.

The analogue signal S_(EA) may be delivered to input 42 of A/D converter40 which is adapted to generate a digital signal S_(MD) having asampling frequency f_(S), as discussed above. The digital signal S_(MD)may be delivered to a band pass filter 240 generating a filtered signalS_(F) in response thereto. The filtered signal S_(F) may be delivered toa rectifier 270, as discussed above in connection with FIG. 6B,delivering a rectified signal S_(R) having sampling frequency f_(S). Therectified signal S_(R) may optionally be delivered to a low pass filter280 so as to produce a digital envelop signal S_(ENV) having samplingfrequency f_(S), as discussed above.

According to an embodiment, the digital envelop signal S_(ENV) may bedelivered to an input 220 of evaluator 230, as discussed above inconnection with FIG. 6B and FIG. 7 (See also FIG. 16). The digitalenvelop signal S_(ENV) may be delivered to an input of a peak detector310. The peak detector 310 may operate to deliver detected signal peaksor detected signal peak values Ap to an output 315 in response to thedigital envelop signal S_(ENV). As mentioned above, digital signalprocessing may advantageously be performed by the data processor 50running program code for causing the data processor 50 to perform thedigital signal processing. According to an embodiment of the inventionthe processor 50 is embodied by a Digital Signal Processor, DSP 50. TheDSP 50 advantageously operates sufficiently fast to enable execution ofthe described digital signal processing on received signal SENv havingthe same or substantially the same sampling frequency f_(S) as deliveredby A/D converter 40. The feature of performing the signal processing onsignals at the sampling frequency f_(S) ensures advantageously accuratepeak value detection. It may also be possible to provide a decimatorbefore the peak value detector so as to detect peak values on adecimated signal having a lower sampling frequency. However, testsperformed by the inventor indicate that performing peak value detectionon a signal at the higher sampling frequency f_(S) advantageouslyensures more accurate peak value detection.

The detected signal peaks or detected signal peak values Ap may bedelivered from the peak detector output 315 to an input 320 of anoptional echo suppresser 330. Alternatively, the detected signal peaksor detected signal peak values Ap may be delivered from the peakdetector output 315 to an Input 340 of a log generator 350. The loggenerator 350 is adapted to generate the logarithmic amplitude valuescorresponding to the amplitude of the received detected signal peaks ordetected signal peak values Ap. Hence, an output 360 of log generator350 is adapted to deliver logarithmic amplitude values. A value sorter370 is adapted to receive the logarithmic amplitude values and to sortthe received the logarithmic amplitude values into amplitude binscorresponding to the received logarithmic amplitude values. Hence, thevalue sorter 370 may be adapted to deliver sorted amplitude valuesA_(P), e.g. in the form of a table 470 or cumulative histogram table530, as discussed and illustrated in connection with FIGS. 13B and/or13C above.

A Peak Value Establisher 375 may be adapted to establish arepresentative peak value A_(PR) in dependence on the sorted peakamplitude values Ap and the certain amount R of revolution of themonitored rotating part. As mentioned above, in connection with FIG.11B, the detector 450 may generate a signal indicative of the amount ofrevolution R, and the duration of measurement may be controlled solelyin dependence on the amount of revolution of the rotatable part 8,irrespective of time. Alternatively, the duration T_(Pm) of themeasurement session may be controlled in dependence of time informationprovided by the clock 190 (FIG. 5) in conjunction with speed of rotationinformation f_(ROT) delivered by detector 450 so that the durationT_(Pm) is adapted to ensure that the monitoring is performed for thedesired amount of rotation n*R. In this connection it is noted that R isa positive number larger than one, and n is a positive number equal toone (1) or larger than one (1). The parameter R may be an integer, butit may alternatively be a decimal number. As discussed above, theparameter values R and n may be preset by the manufacturer of apparatus14, and these values may be stored in the non-volatile memory 52 or inthe non-volatile memory 60 (See FIG. 2A). Alternatively, the parametervalues R and n may be set by the user of the apparatus 14 prior toperforming a measurement session, as discussed in connection with FIG.11A above. The parameter values R and n may be set by the user by meansof the user interface 102, 107 described in connection with FIG. 2A.

The Peak Value Establisher 375 may be adapted to deliver therepresentative peak value A_(PR) on an output 378 (See FIG. 16) allowingthe generated representative peak value A_(PR) to be delivered todisplay 106 or to port 16.

Accordingly, with reference to FIG. 16, an embodiment of the apparatus14 includes a peak detector 310 co-operating with log generator 350, avalue sorter 370 and a Representative Peak Value Establisher 375 so asto perform the method described in connection with FIGS. 11A, 118 and12A above.

According to a preferred embodiment, the apparatus 14 also includes anecho suppresser 330, as discussed above in connection with FIG. 16. Theecho suppresser 330, also referred to as burst rejector 330, may becoupled to receive the detected peak values A_(P) from peak detector310. The apparatus 14 including burst rejector 330 may be adapted toperform the method described in connection with FIG. 12B. Hence, burstrejector 330 may be adapted to deliver output peak values A_(PO) on aburst rejector output 333 in response to received detected peak valuesA_(P). The burst rejector 330 may be adapted to control the delivery ofsaid output peak values A_(PO) such that said output peak values A_(PO)are delivered at a delivery frequency f_(es), wherein

the delivery frequency f_(es)=e*f_(ROT), wherein

f_(ROT) is said speed of rotation, and

e is a factor having a predetermined value.

What is claimed is:
 1. A method of operating an apparatus for analysingthe condition of a machine having a part rotating with a speed ofrotation (f_(ROT)), comprising the steps of: receiving a first digitalsignal (S_(MD), S_(R), S_(F)) dependent on mechanical vibrationsemanating from rotation of said part; analysing said first digitalsignal so as to detect peak amplitude values (Ap) during a finite timeperiod (T_(Pm)), said finite time period corresponding to a certainamount (R) of revolution of said rotatable part; said certain amount (R)of revolution corresponding to more than one revolution of saidmonitored rotatable part; defining a plurality (N_(R)) of amplituderanges; sorting said detected peak amplitude values (Ap) intocorresponding amplitude ranges so as to reflect occurrence (N) ofdetected peak amplitude values (Ap) within said plurality of amplituderanges; estimating a representative peak amplitude value (A_(PR)) independence on said sorted peak amplitude values (Ap) and said certainamount (R).
 2. The method according to claim 1, further comprisingdelivering said representative peak amplitude value (A_(PR)) to a userinterface for presentation to a user.
 3. A computer program forcontrolling the operation of an apparatus for analysing the condition ofa machine having a part which is rotatable with a speed of rotation(f_(ROT)), the computer program comprising: computer readable code meanswhich, when run on an analysis apparatus, causes the computer to performthe steps of claim
 1. 4. An apparatus for analysing the condition of amachine having a part rotating with a speed of rotation (f_(ROT)),comprising: means for receiving a first digital signal (S_(RED), S_(MD),S_(ENV)) dependent on mechanical vibrations emanating from rotation ofsaid part; means for analysing said first digital signal (S_(RED),S_(MD), S_(ENV)) so as to detect peak amplitude values (Ap) during afinite time period (Pm), said finite time period corresponding to acertain amount (R) of revolution of said rotatable part; said certainamount (R) of revolution corresponding to more than one revolution ofsaid monitored rotatable part; means for sorting said detected peakamplitude values (Ap) into a plurality (N_(R)) of correspondingamplitude ranges so as to reflect occurrence (N) of detected peakamplitude values (Ap) within said plurality of amplitude ranges; andmeans for estimating a representative peak amplitude value (A_(PR)) independence on said sorted peak amplitude values (Ap) and said certainamount (R).
 5. An apparatus for analysing the condition of a machinehaving a part rotating with a speed of rotation (f_(ROT)), comprising:an input for receiving a first digital signal (S_(MD)) dependent onmechanical vibrations emanating from rotation of said part; a peakdetector (310) coupled to said input, said peak detector (310) beingadapted to detect peak values (A_(P)) in said received first digitalsignal (S_(MD), S_(F), S_(R), S_(ENV)), and a burst rejector (330) isadapted to deliver output peak values (A_(PO)) on a burst rejectoroutput (333) in response to said detected peak values (A_(p)); andwherein said burst rejector is adapted to control the delivery frequencyof said output peak values (A_(P), A_(PO)) such that said output peakvalues (A_(P), A_(PO)) are delivered at a delivery frequency of f_(es),wherein f_(es)=e*f_(ROT), wherein f_(ROT) is said speed of rotation, ande is a factor having a predetermined value.